{"data":{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40841999", "kind": "science-record", "revision": 1, "content_hash": "sha256:062e1afd7961e84074f05e3b750838c58d12f2ebf54256562296933ab9f338cf", "created_at": "2026-11-01T10:25:52Z", "updated_at": "2026-11-01T10:25:52Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Revelation of prognosis and tumor microenvironment of colorectal cancer based on genes related to antibody-dependent cellular phagocytosis and single-cell landscape.", "doi": "10.1186/s12014-025-09553-5", "pmid": "40841999", "authors": null, "journal": "Clinical proteomics", "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": 7.0, "unit": "feature genes", "tolerance": null, "source": "chars 1659-1752 of source sha256 c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0"}, "evidence": [{"asset": "source:pmid:40841999", "locator": "chars 1659-1752 of source sha256 c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "quote": "This project created a prognostic model based on 7 feature genes using the TCGA training set."}]}], "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:40841999"], "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:40841999", "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:40841999' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40841999", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12014-025-09553-5", "sha256": "sha256:c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12014-025-09553-5", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:40841999 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:40841999"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40841999"]}, "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": "0a0261f1f8d12bb77d8b32926b36322a81624e57a35044b30367720a06a9d1b6", "source_hash": "c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "raw_response_sha256": "sha256:fd1ab165c0684ff9201a37bac3580f9839bed95041b9b3f5f648fba7110df597", "raw_response_chars": 3703}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "c88effefb3f8183d8b5886fc2d177f51af6b06914661ef494cb46781ec284522", "source_hash": "c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "raw_response_sha256": "sha256:8272df1d0c01d8815194787fed4129ff204689650c5bd1f8eac9e3c7f3068115", "raw_response_chars": 70605}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "f0be83fce6de94ba7de1fac5ce45f167a39636e437898d307e106c43cd2cce8d", "source_hash": "c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "raw_response": "{\"parent_value\":7,\"unit\":\"feature genes\",\"evidence\":\"This project created a prognostic model based on 7 feature genes using the TCGA training set.\",\"target_result\":\"The paper states that the prognostic model was based on 7 feature genes.\",\"number_stated\":true}", "reading": {"parent_value": 7, "unit": "feature genes", "evidence": "This project created a prognostic model based on 7 feature genes using the TCGA training set.", "target_result": "The paper states that the prognostic model was based on 7 feature genes.", "number_stated": true, "source_locator": "chars 1659-1752 of source sha256 c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0"}, "recorded_at": "2026-10-31T15:31:53.879620+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "b8587c2e7217e3c98a881611f91cc53a00881917a71a2d95695216e6daa6b157", "source_hash": "c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result main finding. Source abstract/results says prognostic model based on 7 feature genes, genes across 8 cell clusters. Which is \"headline numerical result\" likely 7? Need carefully infer. User asks target generic: headline numerical result paper states for main finding. Need report value paper itself states for registered target, exact contiguous quote with number and attribution.\n\nPotential candidates:\n- \"This project created a prognostic model based on 7 feature genes using the TCGA training set.\" This is main finding headline, perhaps model based on 7 genes.\n- \"the 7 feature genes were examined to be expressed across 8 cell clusters...\" Main findings.\nCould headline numerical result be AUC/C-index/HR absent? Source truncated perhaps no model performance numbers. Registered target likely benchmark asks extract headline numerical result, expected 7 feature genes perhaps unit \"feature genes\". Need parse wording. They explicitly instruct \"single numerical result that a replication ... has to reproduce.\" Main finding is prognostic model based on 7 feature genes. Thus number 7, unit \"feature genes\". Exact quote sentence.\n\nNeed output fields:\nparent_value 7\nunit \"feature genes\"\nevidence exact contiguous quotation: \"This project created a prognostic model based on 7 feature genes using the TCGA training set.\"\ntarget_result perhaps \"The prognostic model was created based on 7 feature genes using the TCGA training set.\" But they demand headline number only maybe target_result perhaps target description. Schema includes target_result. We can put \"Prognostic model based on 7 feature genes using the TCGA training set.\" Yet instruction report headline number only could imply parent_value only, unit, evidence, target_result. JSON necessarily. Maybe target_result can state what text does state instead. number_stated true.\n\nNeed ensure evidence quote contains number. Exact punctuation. Unit printed \"feature genes\". Is \"7 feature genes\" unit. Yes.\n\nCould target be 8 cell clusters? Main finding says 7 model genes and 8 clusters. Which is \"headline numerical result\"? Let's investigate likely task conventions. Registered target phrased \"the headline numerical result the paper states for its main finding.\" They expect identify a numerical result. In abstracts, often first results sentence says \"created prognostic model based on 7 feature genes\". That's headline. The question is perhaps generated around \"registered target\" that is semantically generic, and source text may have key number. We need select likely number. Let's inspect abstract. Title. Abstract Background etc. Results:\n\"This project created a prognostic model based on 7 feature genes using the TCGA training set. The K-M survival curves and ROC curves indicated that the model, as well as the nomogram, was capable of accurately predicting prognosis for CRC patients. Based on scRNA-seq data analysis, the 7 feature genes were examined to be expressed across 8 cell clusters (...). ...\"\nConclusion. Main numerical headline = model based on 7 feature genes. Definitely.\n\nShould evidence quote whole clause. Whole sentence exact. target_result perhaps \"A prognostic model based on 7 feature genes was created using the TCGA training set.\" Fine.\n\n\"Report the headline number only: the value the paper itself states for the registered target\" Means don't include ancillary numbers. Evidence necessarily one sentence with 7 and perhaps no other number. It has TCGA (not numeric). Good.\n\nJSON valid, no markdown.</think>\n\n{\"parent_value\":7,\"unit\":\"feature genes\",\"evidence\":\"This project created a prognostic model based on 7 feature genes using the TCGA training set.\",\"target_result\":\"A prognostic model based on 7 feature genes was created using the TCGA training set.\",\"number_stated\":true}", "reading": {"parent_value": 7, "unit": "feature genes", "evidence": "This project created a prognostic model based on 7 feature genes using the TCGA training set.", "target_result": "A prognostic model based on 7 feature genes was created using the TCGA training set.", "number_stated": true, "source_locator": "chars 1659-1752 of source sha256 c1f4e4e22d37c05464f50ee0247c877e93a496a2dfac2c2dbeefabe8159852e0"}, "recorded_at": "2026-10-31T15:31:54.266801+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "A prognostic model based on 7 feature genes was developed using the TCGA training set and evaluated with Kaplan-Meier survival curves and ROC curves.", "minimax_alt": "The headline numerical result was a prognostic model based on 7 feature genes created using the TCGA training set; Kaplan-Meier survival curves and ROC curves indicated that the model and nomogram accurately predicted prognosis for CRC patients.", "decisive": false}, "analysis_methods": {"minimax": ["univariate Cox regression analysis", "LASSO Cox regression analysis", "multivariate Cox regression analysis", "Kaplan-Meier survival analysis", "receiver operating characteristic (ROC) curve analysis"], "minimax_alt": ["univariate Cox regression", "LASSO Cox regression", "multivariate Cox regression", "nomogram construction based on clinical information and risk scoring", "Kaplan-Meier (K-M) survival analysis", "receiver operation characteristic (ROC) curve analysis", "AUCell R package scoring of individual single cells"], "decisive": false}, "statistical_method": {"minimax": "multivariate Cox regression analysis", "minimax_alt": "Univariate Cox and LASSO Cox regression analyses were used to screen genes, multivariate Cox regression analysis was used to construct the prognostic model, and Kaplan-Meier (K-M) survival curves and receiver operation characteristic (ROC) curves were used to evaluate its prognostic value.", "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:15a81dbbdd319086a74bb6909617ea454d5e7e8423194082ece3530564d1ecc4", "type": "sep_package", "label": "SEP v1 package for pmid:40841999"}], "activities": [{"id": "activity:conversion:pmid:40841999", "type": "conversion", "used": ["package:15a81dbbdd319086a74bb6909617ea454d5e7e8423194082ece3530564d1ecc4"], "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": "ceb135e4-49a2-4951-92ee-60432b1651df", "parent_hash": "15a81dbbdd319086a74bb6909617ea454d5e7e8423194082ece3530564d1ecc4", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40841999 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:40841999' does not resolve to a declared asset", "targets"]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T01:34:21+00:00","total_papers":5529,"total_assays_tracked":29,"automatable_assay_families":6,"validated":true,"caveat_count":9,"blocking_caveats":5,"caveats":[{"code":"low_evidence_dominates","basis":["4,152 of 5,529 classifications (75.1%) matched no cue evidence and sit at the 0.05 floor.","34 of 230 data_only calls (14.8%) are in that group."],"claim":"Work type and confidence bands","gloss":"Most records were classified from their title and framing alone, with assay-cue coverage at zero.","detail":"Most classifications in this run rest on no matched evidence at all. At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. Timing awaits the first executed replication.","4,407 of 5,529 records (79.7%) model to 0.00 hours because no assay was matched, which the ranking then reads as \"cheapest\".","0 of 10 shortlisted records carry a 0.00-hour estimate."],"claim":"Estimated replication runtime","gloss":"The hour figures are estimates built from assay mentions; timing awaits the first executed replication.","detail":"The hour figures are a cost model derived from the bench steps implied by each matched assay family. The first executed replication will supply measured timing. Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}