Corpus Engine Towards a reproducible .science file.
← All .science files

pmid:40853516

Identification of novel cholesterol metabolism-related biomarkers for thyroid cancer to predict the prognosis, immune infiltration, and drug sensitivity.

Discover oncology · 2025 doi:10.1007/s12672-025-03483-2

Paper

partial

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:40853516
kind
science-record
content_hash
sha256:c96029e3b6bd69a5b6ca6f6e1b9a8ad118ca09fd49191365a4aaa16f2523500e
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T10:25:52Z
updated_at
2026-11-01T14:01:46Z
generator object · 3 fields
name
corpus-assay-engine
converter
sep_to_sci_v1
source_package_schema
urn:bntrg:sep:1.0.0
paper object · 10 fields
state
partial
title
Identification of novel cholesterol metabolism-related biomarkers for thyroid cancer to predict the prognosis, immune infiltration, and drug sensitivity.
doi
10.1007/s12672-025-03483-2
pmid
40853516
authors
null
journal
Discover oncology
year
2025
abstract
null
claims array · 1 item
[0] object · 6 fields
id
claim-1
statement
the headline numerical result the paper states for its main finding
kind
quantitative
state
complete
target object · 4 fields
value
11.41
unit
times
tolerance
null
source
chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:40853516
locator
chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
quote
We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.
gaps array · 2 items
[0]
abstract
[1]
authors
experiment object · 8 fields
state
partial
objective
the headline numerical result the paper states for its main finding
steps array · 3 items
[0] object · 13 fields
id
read_published_estimate
order
1
name
Read the published estimate and its interval from the source
kind
other
state
complete
blocked_on
null
description
The number a replication must land on, and the sentence it came from.
parameters object · 0 fields
inputs array · 1 item
[0]
source:pmid:40853516
outputs array · 1 item
[0]
the published estimate, its unit and its interval
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
id
obtain_source_data
order
2
name
Obtain the source data behind the published result
kind
data-preparation
state
blocked
blocked_on
data:not_downloaded
description
The published result cannot be recomputed without the data the paper analysed.
parameters object · 0 fields
inputs array · 0 items
outputs array · 1 item
[0]
the source data with its provenance
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
id
run_analysis
order
3
name
Run the analysis programme
kind
analysis
state
blocked
blocked_on
no owned computational capability is bound to this experiment
description
Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:40853516
parameters object · 0 fields
inputs array · 0 items
outputs array · 1 item
[0]
the registered result
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 3 items
[0]
step:obtain_source_data blocked on data:not_downloaded
[1]
step:run_analysis blocked on no owned computational capability is bound to this experiment
[2]
step:run_analysis input 'materials:the source data behind the published result in pmid:40853516' does not resolve to a declared asset
data object · 3 fields
state
partial
assets array · 2 items
[0] object · 15 fields
id
source:pmid:40853516
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.1007/s12672-025-03483-2
sha256
sha256:a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.1007/s12672-025-03483-2
version
null
note
Source read by the package builder: full_text.
structure object · 1 field
access_state
full_text
[1] object · 16 fields
id
asset:table:pmid:40853516:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:1044b1ab274eee721fc07b508df27f164f5b179483575d136b65d820f431aa1f
bytes
1479
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[3]/table-wrap[1]#Tab1
version
null
note
Baseline characteristics
structure object · 5 fields
pmcid
PMC12378849
section_index
3
section_title
Data sources and pre-processing
row_count
25
column_count
6
table object · 8 fields
label
Table 1
caption
Baseline characteristics
rows array · 25 items
[0] array · 6 items
[0]
[1]
level
[2]
Overall
[3]
Training set
[4]
Test set
[5]
p
[1] array · 5 items
[0]
n
[1]
497
[2]
348
[3]
149
[4]
[2] array · 5 items
[0]
Age
[1]
46
[2]
46
[3]
48
[4]
0.713
[3] array · 4 items
[0]
(median [IQR])
[1]
[35.00, 58.00]
[2]
[36.00, 57.25]
[3]
[34.00, 59.00]
[4] array · 6 items
[0]
gender (%)
[1]
female
[2]
363 (73.0)
[3]
248 (71.3)
[4]
115 (77.2)
[5]
0.211
[5] array · 6 items
[0]
[1]
male
[2]
134 (27.0)
[3]
100 (28.7)
[4]
34 (22.8)
[5]
[6] array · 6 items
[0]
T (%)
[1]
T1
[2]
142 (28.6)
[3]
103 (29.6)
[4]
39 (26.2)
[5]
0.746
[7] array · 6 items
[0]
[1]
T2
[2]
162 (32.6)
[3]
109 (31.3)
[4]
53 (35.6)
[5]
[8] array · 6 items
[0]
[1]
T3
[2]
169 (34.0)
[3]
118 (33.9)
[4]
51 (34.2)
[5]
[9] array · 6 items
[0]
[1]
T4
[2]
22 ( 4.4)
[3]
16 ( 4.6)
[4]
6 ( 4.0)
[5]
[10] array · 6 items
[0]
[1]
TX
[2]
2 ( 0.4)
[3]
2 ( 0.6)
[4]
0 ( 0.0)
[5]
[11] array · 6 items
[0]
N (%)
[1]
N0
[2]
227 (45.7)
[3]
166 (47.7)
[4]
61 (40.9)
[5]
0.222
[12] array · 6 items
[0]
[1]
N1
[2]
221 (44.5)
[3]
152 (43.7)
[4]
69 (46.3)
[5]
[13] array · 6 items
[0]
[1]
NX
[2]
49 ( 9.9)
[3]
30 ( 8.6)
[4]
19 (12.8)
[5]
[14] array · 6 items
[0]
M (%)
[1]
M0
[2]
282 (56.7)
[3]
197 (56.6)
[4]
85 (57.0)
[5]
0.566
[15] array · 6 items
[0]
[1]
M1
[2]
8 ( 1.6)
[3]
4 ( 1.1)
[4]
4 ( 2.7)
[5]
[16] array · 6 items
[0]
[1]
MX
[2]
206 (41.4)
[3]
146 (42.0)
[4]
60 (40.3)
[5]
[17] array · 6 items
[0]
[1]
Unknow
[2]
1 ( 0.2)
[3]
1 ( 0.3)
[4]
0 ( 0.0)
[5]
[18] array · 6 items
[0]
stage (%)
[1]
I
[2]
279 (56.1)
[3]
199 (57.2)
[4]
80 (53.7)
[5]
0.766
[19] array · 6 items
[0]
[1]
II
[2]
52 (10.5)
[3]
38 (10.9)
[4]
14 ( 9.4)
[5]
[20] array · 6 items
[0]
[1]
III
[2]
111 (22.3)
[3]
76 (21.8)
[4]
35 (23.5)
[5]
[21] array · 6 items
[0]
[1]
IV
[2]
53 (10.7)
[3]
34 ( 9.8)
[4]
19 (12.8)
[5]
[22] array · 6 items
[0]
[1]
Unknow
[2]
2 ( 0.4)
[3]
1 ( 0.3)
[4]
1 ( 0.7)
[5]
[23] array · 6 items
[0]
PFI (%)
[1]
0
[2]
446 (89.7)
[3]
313 (89.9)
[4]
133 (89.3)
[5]
0.946
[24] array · 6 items
[0]
[1]
1
[2]
51 (10.3)
[3]
35 (10.1)
[4]
16 (10.7)
[5]
locator
section[3]/table-wrap[1]#Tab1
gaps array · 1 item
[0]
asset:source:pmid:40853516 not verified
analysis object · 4 fields
state
absent
methods array · 0 items
targets array · 0 items
gaps array · 2 items
[0]
method
[1]
targets
capability object · 3 fields
state
absent
requirements array · 0 items
gaps array · 1 item
[0]
capability
readiness object · 8 fields
state
partial
tier
null
blocked_on
null
axes object · 0 fields
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 2 items
[0]
source:pmid:40853516
[1]
asset:table:pmid:40853516:1
steps array · 1 item
[0]
read_published_estimate
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 1 item
[0]
xml
capabilities array · 0 items
data_gaps array · 1 item
[0]
source:pmid:40853516
gaps array · 1 item
[0]
corpus_record_absent
review object · 5 fields
state
partial
machine_critique object · 7 fields
status
blocked
providers array · 2 items
[0] object · 7 fields
provider
minimax
model
MiniMax-M3.1-Flash
prompt_version
full-text-reading-v1
prompt_hash
02b8f2e431a4054095c83633a2f956831a33f4776f0ff8c58512d0d4def5c374
source_hash
a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
raw_response_sha256
sha256:4070b89a8d0a4a918f67f94496f81fa5ab36457fa7a32e4e38d45ccd8c11dec2
raw_response_chars
3919
[1] object · 7 fields
provider
minimax_alt
model
MiniMax-M3
prompt_version
full-text-reading-v1
prompt_hash
5df956a123d40d499b05f58093f51874cce1980372be748c5ad55f768c394e38
source_hash
a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
raw_response_sha256
sha256:ac5d8f07a8550793ecbaaa604aca9c8ab7916504bdce27c126c34a081ccf8f7b
raw_response_chars
65009
target_providers array · 2 items
[0] object · 8 fields
provider
minimax
model
MiniMax-M3.1-Flash
prompt_version
replication-target-v2
prompt_hash
6ba719aba2c8425c9bcfbce5279ccf9d12dd3a0cf904e65c36347b496676cbc8
source_hash
a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
raw_response
{"parent_value":11.41,"unit":"times","evidence":"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.","target_result":"The mortality rate of high-risk patients increased by 11.41 times.","number_stated":true}
reading object · 6 fields
parent_value
11.41
unit
times
evidence
We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.
target_result
The mortality rate of high-risk patients increased by 11.41 times.
number_stated
true
source_locator
chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
recorded_at
2026-10-31T15:31:46.093664+00:00
[1] object · 8 fields
provider
minimax_alt
model
MiniMax-M3
prompt_version
replication-target-v2
prompt_hash
206e76512645b4c66f554c035b7926805cd9dac7b3df10ef547305cfb0b90489
source_hash
a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
raw_response
<think>We need answer JSON object only. Need identify single numerical result headline main finding registered target. Paper abstract: "We found that the mortality rate of high-risk patients increased by 11.41 times" likely headline numerical result. Need report value, unit as printed. Unit? "times" perhaps unit. Evidence exact contiguous quote containing number, whole clause so attribution check. Need likely quote: "We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced." parent_value 11.41, unit "times". target_result maybe "The mortality rate of high-risk patients increased by 11.41 times." number_stated true. But let's carefully parse instructions. "single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints. The evidence must be an exact, contiguous quotation from SOURCE TEXT that contains the number; do not shorten it, do not add an ellipsis and do not paraphrase it. Attribution may be carried by text's own wording: a number may be attached to target by parenthetical list, by word 'respectively', or by words that name target directly. When that is how text links them, quote whole clause so reader can check attribution." Headline main finding perhaps number of CMRGs = 6? Or mortality increased 11.41 times. "headline numerical result the paper states for its main finding" likely abstract's quantitative outcome. Need choose. The paper title main finding biomarkers, six genes. But single numerical result replication target. Could be 11.41 times as headline quantitative result. They ask unit paper prints. likely "times". The answer schema parent_value maybe 11.41. Evidence quote exact. target_result concise. Ensure JSON valid, no markdown. Could unit be "times" or "fold"? Paper prints "times", so times. Exact quote could include sentence. Evidence should quote whole clause. "We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced." Exact contiguous. Target result perhaps "mortality rate of high-risk patients increased by 11.41 times". The "headline number only" perhaps target_result shouldn't include other results. Fine. Need no extra prose.</think> {"parent_value":11.41,"unit":"times","evidence":"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.","target_result":"The mortality rate of high-risk patients increased by 11.41 times.","number_stated":true}
reading object · 6 fields
parent_value
11.41
unit
times
evidence
We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.
target_result
The mortality rate of high-risk patients increased by 11.41 times.
number_stated
true
source_locator
chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba
recorded_at
2026-10-31T15:31:48.398834+00:00
agreement
false
disagreements object · 2 fields
analysis_methods object · 3 fields
minimax array · 13 items
[0]
univariate Cox regression
[1]
least absolute shrinkage and selection operator (LASSO)
[2]
Lasso-Cox regression
[3]
nomogram
[4]
differential expression analysis using DESeq2
[5]
Wilcoxon test
[6]
KEGG and GO enrichment analysis
[7]
gene set enrichment analysis (GSEA)
[8]
single-sample gene set enrichment analysis (GSVA)
[9]
ssGSEA
[10]
Estimate, EPIC, CIBERSORT, and MCPcounter immune-cell estimation
[11]
pRRophetic
[12]
Wilcoxon signed-rank test
minimax_alt array · 18 items
[0]
univariate Cox regression
[1]
least absolute shrinkage and selection operator (LASSO)
[2]
Lasso-Cox regression
[3]
random training/validation split
[4]
nomogram
[5]
DESeq2 differential-expression analysis
[6]
Wilcoxon test
[7]
KEGG pathway enrichment analysis
[8]
Gene Ontology functional annotation
[9]
Gene Set Enrichment Analysis (GSEA)
[10]
Gene Set Variation Analysis (GSVA)
[11]
single-sample Gene Set Enrichment Analysis (ssGSEA)
[12]
Estimate
[13]
EPIC
[14]
CIBERSORT
[15]
MCPcounter
[16]
pRRophetic
[17]
Wilcoxon signed-rank test
decisive
false
statistical_method object · 3 fields
minimax
Lasso-Cox regression
minimax_alt
univariate Cox regression and least absolute shrinkage and selection operator (LASSO)
decisive
true
agreement_basis object · 2 fields
policy
decisive_fields
decisive_fields array · 4 items
[0]
work_type
[1]
number_stated
[2]
parent_value
[3]
unit
blinded
true
human_critique object · 5 fields
status
not_run
reviewer
null
signed_at
null
conflict_checked
false
commentary
null
stages array · 7 items
[0] object · 4 fields
key
target_materials
status
pending
reason
null
evidence
null
[1] object · 4 fields
key
independent_readings
status
blocked
reason
The independent readings are incomplete or disagree; the source evidence must resolve the difference.
evidence object · 1 field
provider_errors array · 0 items
[2] object · 4 fields
key
source_resolution
status
pending
reason
null
evidence
null
[3] object · 4 fields
key
protocol_reconstruction
status
pending
reason
null
evidence
null
[4] object · 4 fields
key
control_execution
status
pending
reason
null
evidence
null
[5] object · 4 fields
key
control_comparison
status
pending
reason
null
evidence
null
[6] object · 4 fields
key
publication
status
pending
reason
null
evidence
null
gaps array · 2 items
[0]
review.human_critique
[1]
review.machine_critique.blocked
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 1 item
[0] object · 3 fields
id
package:94166ddab9d69156712e9fbff0a47f3b30b23afab04f668aa4b1923830657d2b
type
sep_package
label
SEP v1 package for pmid:40853516
activities array · 1 item
[0] object · 4 fields
id
activity:conversion:pmid:40853516
type
conversion
used array · 1 item
[0]
package:94166ddab9d69156712e9fbff0a47f3b30b23afab04f668aa4b1923830657d2b
agent
agent:corpus-assay-engine
agents array · 3 items
[0] object · 3 fields
id
agent:minimax
type
model
label
minimax
[1] object · 3 fields
id
agent:minimax_alt
type
model
label
minimax_alt
[2] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
source_run_id
run-20261023T122449232913
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:40853516
parent_hash
sha256:da0d91976405a65061b10174808199bb460828b615bf7f0321bf6349e751ea22
fork_of
null
gaps array · 13 items
[0]
abstract
[1]
asset:source:pmid:40853516 not verified
[2]
authors
[3]
capability
[4]
corpus_record_absent
[5]
execution.not_run
[6]
method
[7]
review.human_critique
[8]
review.machine_critique.blocked
[9]
step:obtain_source_data blocked on data:not_downloaded
[10]
step:run_analysis blocked on no owned computational capability is bound to this experiment
[11]
step:run_analysis input 'materials:the source data behind the published result in pmid:40853516' does not resolve to a declared asset
[12]
targets
Complete file
{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40853516", "kind": "science-record", "revision": 2, "content_hash": "sha256:c96029e3b6bd69a5b6ca6f6e1b9a8ad118ca09fd49191365a4aaa16f2523500e", "created_at": "2026-11-01T10:25:52Z", "updated_at": "2026-11-01T14:01:46Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Identification of novel cholesterol metabolism-related biomarkers for thyroid cancer to predict the prognosis, immune infiltration, and drug sensitivity.", "doi": "10.1007/s12672-025-03483-2", "pmid": "40853516", "authors": null, "journal": "Discover oncology", "year": 2025, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "quantitative", "state": "complete", "target": {"value": 11.41, "unit": "times", "tolerance": null, "source": "chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba"}, "evidence": [{"asset": "source:pmid:40853516", "locator": "chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "quote": "We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced."}]}], "gaps": ["abstract", "authors"]}, "experiment": {"state": "partial", "objective": "the headline numerical result the paper states for its main finding", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate and its interval from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The number a replication must land on, and the sentence it came from.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40853516"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data behind the published result", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:not_downloaded", "description": "The published result cannot be recomputed without the data the paper analysed.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the analysis programme", "kind": "analysis", "state": "blocked", "blocked_on": "no owned computational capability is bound to this experiment", "description": "Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:40853516", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the registered result"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40853516' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40853516", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-025-03483-2", "sha256": "sha256:a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1007/s12672-025-03483-2", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}, {"id": "asset:table:pmid:40853516:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:1044b1ab274eee721fc07b508df27f164f5b179483575d136b65d820f431aa1f", "bytes": 1479, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[3]/table-wrap[1]#Tab1", "version": null, "note": "Baseline characteristics", "structure": {"pmcid": "PMC12378849", "section_index": 3, "section_title": "Data sources and pre-processing", "row_count": 25, "column_count": 6}, "table": {"label": "Table 1", "caption": "Baseline characteristics", "rows": [["", "level", "Overall", "Training set", "Test set", "p"], ["n", "497", "348", "149", ""], ["Age", "46", "46", "48", "0.713"], ["(median [IQR])", "[35.00, 58.00]", "[36.00, 57.25]", "[34.00, 59.00]"], ["gender (%)", "female", "363 (73.0)", "248 (71.3)", "115 (77.2)", "0.211"], ["", "male", "134 (27.0)", "100 (28.7)", "34 (22.8)", ""], ["T (%)", "T1", "142 (28.6)", "103 (29.6)", "39 (26.2)", "0.746"], ["", "T2", "162 (32.6)", "109 (31.3)", "53 (35.6)", ""], ["", "T3", "169 (34.0)", "118 (33.9)", "51 (34.2)", ""], ["", "T4", "22 ( 4.4)", "16 ( 4.6)", "6 ( 4.0)", ""], ["", "TX", "2 ( 0.4)", "2 ( 0.6)", "0 ( 0.0)", ""], ["N (%)", "N0", "227 (45.7)", "166 (47.7)", "61 (40.9)", "0.222"], ["", "N1", "221 (44.5)", "152 (43.7)", "69 (46.3)", ""], ["", "NX", "49 ( 9.9)", "30 ( 8.6)", "19 (12.8)", ""], ["M (%)", "M0", "282 (56.7)", "197 (56.6)", "85 (57.0)", "0.566"], ["", "M1", "8 ( 1.6)", "4 ( 1.1)", "4 ( 2.7)", ""], ["", "MX", "206 (41.4)", "146 (42.0)", "60 (40.3)", ""], ["", "Unknow", "1 ( 0.2)", "1 ( 0.3)", "0 ( 0.0)", ""], ["stage (%)", "I", "279 (56.1)", "199 (57.2)", "80 (53.7)", "0.766"], ["", "II", "52 (10.5)", "38 (10.9)", "14 ( 9.4)", ""], ["", "III", "111 (22.3)", "76 (21.8)", "35 (23.5)", ""], ["", "IV", "53 (10.7)", "34 ( 9.8)", "19 (12.8)", ""], ["", "Unknow", "2 ( 0.4)", "1 ( 0.3)", "1 ( 0.7)", ""], ["PFI (%)", "0", "446 (89.7)", "313 (89.9)", "133 (89.3)", "0.946"], ["", "1", "51 (10.3)", "35 (10.1)", "16 (10.7)", ""]], "row_count": 25, "column_count": 6, "numeric_cells": 81, "header_rows": 1, "locator": "section[3]/table-wrap[1]#Tab1"}}], "gaps": ["asset:source:pmid:40853516 not verified"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:40853516", "asset:table:pmid:40853516:1"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40853516"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "02b8f2e431a4054095c83633a2f956831a33f4776f0ff8c58512d0d4def5c374", "source_hash": "a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "raw_response_sha256": "sha256:4070b89a8d0a4a918f67f94496f81fa5ab36457fa7a32e4e38d45ccd8c11dec2", "raw_response_chars": 3919}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "5df956a123d40d499b05f58093f51874cce1980372be748c5ad55f768c394e38", "source_hash": "a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "raw_response_sha256": "sha256:ac5d8f07a8550793ecbaaa604aca9c8ab7916504bdce27c126c34a081ccf8f7b", "raw_response_chars": 65009}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "6ba719aba2c8425c9bcfbce5279ccf9d12dd3a0cf904e65c36347b496676cbc8", "source_hash": "a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "raw_response": "{\"parent_value\":11.41,\"unit\":\"times\",\"evidence\":\"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.\",\"target_result\":\"The mortality rate of high-risk patients increased by 11.41 times.\",\"number_stated\":true}", "reading": {"parent_value": 11.41, "unit": "times", "evidence": "We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.", "target_result": "The mortality rate of high-risk patients increased by 11.41 times.", "number_stated": true, "source_locator": "chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba"}, "recorded_at": "2026-10-31T15:31:46.093664+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "206e76512645b4c66f554c035b7926805cd9dac7b3df10ef547305cfb0b90489", "source_hash": "a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba", "raw_response": "<think>We need answer JSON object only. Need identify single numerical result headline main finding registered target. Paper abstract: \"We found that the mortality rate of high-risk patients increased by 11.41 times\" likely headline numerical result. Need report value, unit as printed. Unit? \"times\" perhaps unit. Evidence exact contiguous quote containing number, whole clause so attribution check. Need likely quote: \"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.\" parent_value 11.41, unit \"times\". target_result maybe \"The mortality rate of high-risk patients increased by 11.41 times.\" number_stated true.\n\nBut let's carefully parse instructions. \"single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints. The evidence must be an exact, contiguous quotation from SOURCE TEXT that contains the number; do not shorten it, do not add an ellipsis and do not paraphrase it. Attribution may be carried by text's own wording: a number may be attached to target by parenthetical list, by word 'respectively', or by words that name target directly. When that is how text links them, quote whole clause so reader can check attribution.\"\n\nHeadline main finding perhaps number of CMRGs = 6? Or mortality increased 11.41 times. \"headline numerical result the paper states for its main finding\" likely abstract's quantitative outcome. Need choose. The paper title main finding biomarkers, six genes. But single numerical result replication target. Could be 11.41 times as headline quantitative result. They ask unit paper prints. likely \"times\". The answer schema parent_value maybe 11.41. Evidence quote exact. target_result concise. Ensure JSON valid, no markdown.\n\nCould unit be \"times\" or \"fold\"? Paper prints \"times\", so times. Exact quote could include sentence. Evidence should quote whole clause. \"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.\" Exact contiguous. Target result perhaps \"mortality rate of high-risk patients increased by 11.41 times\". The \"headline number only\" perhaps target_result shouldn't include other results. Fine.\n\nNeed no extra prose.</think>\n\n{\"parent_value\":11.41,\"unit\":\"times\",\"evidence\":\"We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.\",\"target_result\":\"The mortality rate of high-risk patients increased by 11.41 times.\",\"number_stated\":true}", "reading": {"parent_value": 11.41, "unit": "times", "evidence": "We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced.", "target_result": "The mortality rate of high-risk patients increased by 11.41 times.", "number_stated": true, "source_locator": "chars 1780-1947 of source sha256 a1d56d99a12618e6a050a735de8fe8cc9fb9b188f8f1dcf49964ea80b495c1ba"}, "recorded_at": "2026-10-31T15:31:48.398834+00:00"}], "agreement": false, "disagreements": {"analysis_methods": {"minimax": ["univariate Cox regression", "least absolute shrinkage and selection operator (LASSO)", "Lasso-Cox regression", "nomogram", "differential expression analysis using DESeq2", "Wilcoxon test", "KEGG and GO enrichment analysis", "gene set enrichment analysis (GSEA)", "single-sample gene set enrichment analysis (GSVA)", "ssGSEA", "Estimate, EPIC, CIBERSORT, and MCPcounter immune-cell estimation", "pRRophetic", "Wilcoxon signed-rank test"], "minimax_alt": ["univariate Cox regression", "least absolute shrinkage and selection operator (LASSO)", "Lasso-Cox regression", "random training/validation split", "nomogram", "DESeq2 differential-expression analysis", "Wilcoxon test", "KEGG pathway enrichment analysis", "Gene Ontology functional annotation", "Gene Set Enrichment Analysis (GSEA)", "Gene Set Variation Analysis (GSVA)", "single-sample Gene Set Enrichment Analysis (ssGSEA)", "Estimate", "EPIC", "CIBERSORT", "MCPcounter", "pRRophetic", "Wilcoxon signed-rank test"], "decisive": false}, "statistical_method": {"minimax": "Lasso-Cox regression", "minimax_alt": "univariate Cox regression and least absolute shrinkage and selection operator (LASSO)", "decisive": true}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:94166ddab9d69156712e9fbff0a47f3b30b23afab04f668aa4b1923830657d2b", "type": "sep_package", "label": "SEP v1 package for pmid:40853516"}], "activities": [{"id": "activity:conversion:pmid:40853516", "type": "conversion", "used": ["package:94166ddab9d69156712e9fbff0a47f3b30b23afab04f668aa4b1923830657d2b"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40853516", "parent_hash": "sha256:da0d91976405a65061b10174808199bb460828b615bf7f0321bf6349e751ea22", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:40853516 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40853516' does not resolve to a declared asset", "targets"]}