{"data":{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39883234", "kind": "science-record", "revision": 1, "content_hash": "sha256:6e43131e533f3014b4c2c2dfac8482ba514ff2c17480d26c199383e0b9a71049", "created_at": "2026-11-01T10:25:49Z", "updated_at": "2026-11-01T10:25:49Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "FOXP3 as a prognostic marker and therapeutic target in immunogenic cell death modulation for clear cell renal cell carcinoma.", "doi": "10.1007/s12672-025-01831-w", "pmid": "39883234", "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": 0.781, "unit": "auc", "tolerance": null, "source": "chars 5043-5196 of source sha256 ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840"}, "evidence": [{"asset": "source:pmid:39883234", "locator": "chars 5043-5196 of source sha256 ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "quote": "Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B)."}]}], "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:39883234"], "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:39883234", "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:39883234' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39883234", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-025-01831-w", "sha256": "sha256:ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1007/s12672-025-01831-w", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:39883234 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:39883234"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:39883234"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "passed", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "484a210ced6d4d5e26e4c040eb06b41fbb1ec67b334ad0876b6f38b4b3791130", "source_hash": "ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "raw_response_sha256": "sha256:28463d5dd3127a07db8b035fa6eced3d98b2ceefd28990348eeffbe7a246323b", "raw_response_chars": 5146}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "f5747ca32fe6f2a687fe6f5eaa1138b79b976c2ac23f11293dc87222fc20b514", "source_hash": "ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "raw_response_sha256": "sha256:58b46d4f9edec5307dc07f29f847b1e84f638d3f42cdd2b625a907fc82c8edbc", "raw_response_chars": 48759}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "5f579c41bbe31e7afb3ab55fe8e14ba0f1cf321ee9885faacfa12a4be9d15ebe", "source_hash": "ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "raw_response": "{\"parent_value\":0.781,\"unit\":\"AUC\",\"evidence\":\"Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).\",\"target_result\":\"FOXP3 diagnostic ROC AUC\",\"number_stated\":true}", "reading": {"parent_value": 0.781, "unit": "AUC", "evidence": "Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).", "target_result": "FOXP3 diagnostic ROC AUC", "number_stated": true, "source_locator": "chars 5043-5196 of source sha256 ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840"}, "recorded_at": "2026-10-31T15:22:17.392092+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "e3fda92cbd0255e0780e1b749a3c15e3d4d8305a7f52ec2fd1f0cde8fdd81c28", "source_hash": "ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result paper states for main finding. Source includes multiple numbers. Main finding perhaps FOXP3 AUC 0.781 as headline numerical result? Need infer. They ask \"registered target: the headline numerical result the paper states for its main finding.\" We need report value paper itself states, not calculated. Unit paper prints. Evidence exact contiguous quote containing number and attribution via direct wording. Candidate \"Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).\" Headline numerical result likely AUC 0.781. Could perhaps 11 genes. But paper main finding FOXP3 as prognostic marker and therapeutic target; headline numerical result perhaps AUC 0.781. Need parent_value 0.781, unit maybe \"AUC\" or empty? They say unit must be unit paper prints. AUC is dimensionless and paper prints \"AUC of 0.781.\" Unit likely \"AUC\". Evidence whole clause exact. target_result description perhaps \"FOXP3 has an AUC of 0.781 for distinguishing...\" Need ensure source exact quotation no shorten. Exact contiguous quote. Could quote sentence. \"Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).\" Yes.\n\nQuestion wording nuanced: \"find the single numerical result that a replication of the registered target has to reproduce.\" Maybe target registered is \"headline numerical result the paper states for its main finding.\" Need select one. Other salient numerical: 11 genes, 18 genes, 3464, p &lt;0.001, AUC .781. Main finding is FOXP3. Its quantitative headline is AUC .781. Unit printed maybe no conventional unit. Unit string could be \"AUC\". In schema parent_value numeric.\n\nNeed not include extra. target_result likely \"FOXP3's diagnostic ROC AUC was 0.781.\" But this paraphrases? target_result unrestricted. Evidence exact. number_stated true.\n\nCould unit be \"\" because AUC isn't a unit? User says \"The unit must be the unit the paper prints.\" Paper prints \"AUC\", not a unit exactly. They likely expect unit \"AUC\". We should state \"AUC\". Let's ensure JSON valid, no markdown.</think>\n\n{\"parent_value\":0.781,\"unit\":\"AUC\",\"evidence\":\"Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).\",\"target_result\":\"FOXP3 had an AUC of 0.781 for distinguishing ccRCC from adjacent normal tissues.\",\"number_stated\":true}", "reading": {"parent_value": 0.781, "unit": "AUC", "evidence": "Diagnostic ROC curve indicated that FOXP3 has good accuracy in distinguishing between cancer and adjacent normal tissues, with an AUC of 0.781 (Fig. 6B).", "target_result": "FOXP3 had an AUC of 0.781 for distinguishing ccRCC from adjacent normal tissues.", "number_stated": true, "source_locator": "chars 5043-5196 of source sha256 ef0ca94bfb80c40560513ace0d81acf61eb4f03179ce7ca95ffbfdca9acce840"}, "recorded_at": "2026-10-31T15:22:18.342976+00:00"}], "agreement": true, "disagreements": {"target_result": {"minimax": "FOXP3 had an AUC of 0.781 for distinguishing ccRCC cancer tissue from adjacent normal tissue.", "minimax_alt": "FOXP3 achieved an AUC of 0.781 for distinguishing ccRCC cancer tissue from adjacent normal tissue.", "decisive": false}, "physical_methods": {"minimax": ["FOXP3 knockdown experiments in ccRCC cell lines"], "minimax_alt": ["FOXP3 knockdown in ccRCC cell lines", "Cell proliferation measurement", "Cell migration measurement"], "decisive": false}, "analysis_methods": {"minimax": ["consensus clustering", "principal component analysis (PCA)", "univariate Cox regression analysis", "Kaplan-Meier (KM) curve analysis", "receiver operating characteristic (ROC) curve analysis", "Gene Set Enrichment Analysis (GSEA)", "ESTIMATE", "immune cell infiltration analysis", "functional pathway enrichment analysis", "somatic mutation analysis using the maftools R package", "tumor mutational burden (TMB) analysis", "drug sensitivity analysis using the prophetic package"], "minimax_alt": ["Consensus clustering", "Principal component analysis (PCA) for ICD signature development", "Differential expression analysis using an adjusted p-value threshold of < 0.001", "Univariate Cox regression", "Receiver operating characteristic (ROC) curve analysis", "Kaplan-Meier (KM) survival analysis", "Gene set enrichment analysis (GSEA)", "ESTIMATE", "maftools somatic mutation profiling", "Tumor mutational burden comparison", "prophetic-package IC50 analysis", "TCIA immune-therapy response comparison"], "decisive": false}}, "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": "passed", "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.passed"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:0702b507456f621de667a0342b032c46d0b4bc6c5e0e604f32e776437281e7a2", "type": "sep_package", "label": "SEP v1 package for pmid:39883234"}], "activities": [{"id": "activity:conversion:pmid:39883234", "type": "conversion", "used": ["package:0702b507456f621de667a0342b032c46d0b4bc6c5e0e604f32e776437281e7a2"], "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": "1881d9fe-1847-4ed6-9280-97b997453cc8", "parent_hash": "0702b507456f621de667a0342b032c46d0b4bc6c5e0e604f32e776437281e7a2", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:39883234 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.passed", "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:39883234' 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":"2026-11-04T00:35:31+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}}}