Single-cell and spatial transcriptomics reveal P4HA2-mediated radiotherapy resistance mechanisms in breast cancer.

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"data_gaps": ["source:pmid:41424847"]}, "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": "7f08cf6a7a98049061f735d89b1752a58502bbebcd325f93d35d78e44638c1f2", "source_hash": "69338273ac29bd2d63542fdfa7174bf5f9489056feca391ba3b7c856c35b6757", "raw_response_sha256": "sha256:61f3e7f7d4d3da18684de051b78b9ade943453366d8b1fad1f870f11aafbcec3", "raw_response_chars": 2812}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "c84bcd5588775f1a8be065a09968322ade1d1448e1a0a4ff5a32c1fbdeb10b74", "source_hash": "69338273ac29bd2d63542fdfa7174bf5f9489056feca391ba3b7c856c35b6757", "raw_response_sha256": "sha256:01e1899b61889fd6b58514bebfb8c99333756707fff46ea920081cf25a1a7db0", "raw_response_chars": 75022}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "d8fe23a8dbdd1c4d4fb9c7397a0801842c6e6335f30967d99a6e864401f40133", "source_hash": "69338273ac29bd2d63542fdfa7174bf5f9489056feca391ba3b7c856c35b6757", "raw_response": "{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"The text states that P4HA2 is a potential therapeutic target that sensitizes breast cancer to radiotherapy and that the RR gene panel and SSRR model provide insights into resistance mechanisms and prognostic stratification; it does not state a headline numerical result for this main finding.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "The text states that P4HA2 is a potential therapeutic target that sensitizes breast cancer to radiotherapy and that the RR gene panel and SSRR model provide insights into resistance mechanisms and prognostic stratification; it does not state a headline numerical result for this main finding.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:16:39.483526+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "27109998fbe838abeebfc95181e9a13ee302b28d7d8311444c0b0d9eea1d3a17", "source_hash": "69338273ac29bd2d63542fdfa7174bf5f9489056feca391ba3b7c856c35b6757", "raw_response": "<think>We need answer JSON only. Need interpret registered target headline numerical result paper states for main finding. Source supplied is partial abstract/methods/results. Need find single numerical result. Perhaps 318 genes? Main finding? Need exact contiguous quote with number and target attribution. We need identify headline numerical result. Registered target: \"the headline numerical result the paper states for its main finding\". Could be number 318 genes with causal relationships across 24 GWAS cohorts. But main finding headline perhaps in abstract there are no numbers except maybe absent. Source includes 24, 318. Need decide which is single numerical result replication registered target has to reproduce. They want headline number likely \"318 genes\" as key result? Yet \"headline numerical result the paper itself states for the registered target\" registered target broad main finding. Need not calculate. Source text says \"Across 24 GWAS cohorts, we identified 318 genes with causal relationships to breast cancer (Table S3).\" This is explicit numerical result. Evidence exact clause. Unit \"genes\". parent_value 318. target_result perhaps same. Is this \"headline numerical result\" perhaps 318. Let's parse prompt likely benchmark for extracting parent numerical result from paper, target is registered. They provide source maybe article excerpt and ask number. Need find exact quote. Main finding perhaps Mendelian randomization finding: 318 genes. Other numbers are methods references and tool versions. 24 GWAS cohorts is sample count, not headline. 318 is result. Could mention target_result \"318 genes with causal relationships to breast cancer\". Evidence exact quotation whole sentence because attribution. Unit printed? The paper prints \"genes\" after number, yes unit \"genes\". JSON valid.\n\nNeed ensure evidence exact contiguous quote from source, no alteration. \"Across 24 GWAS cohorts, we identified 318 genes with causal relationships to breast cancer (Table S3).\" Contains another number 24 but parent headline 318. The prompt says quote whole clause when linked via wording. Could use exact sentence. unit \"genes\". target_result string. number_stated true.\n\nCould headline numerical result perhaps \"24 breast cancer-related GWAS cohorts\" from MR analysis? Yet outcome says identified 318 genes. Replication of registered target likely must reproduce headline result, likely 318. Let's answer only JSON.</think>\n\n{\"parent_value\":318,\"unit\":\"genes\",\"evidence\":\"Across 24 GWAS cohorts, we identified 318 genes with causal relationships to breast cancer (Table S3).\",\"target_result\":\"318 genes with causal relationships to breast cancer\",\"number_stated\":true}", "reading": {"parent_value": 318, "unit": "genes", "evidence": "Across 24 GWAS cohorts, we identified 318 genes with causal relationships to breast cancer (Table S3).", "target_result": "318 genes with causal relationships to breast cancer", "number_stated": true, "source_locator": "chars 3654-3756 of source sha256 69338273ac29bd2d63542fdfa7174bf5f9489056feca391ba3b7c856c35b6757"}, "recorded_at": "2026-10-31T15:16:40.624843+00:00"}], "agreement": false, "disagreements": {"work_type": {"minimax": "analysis_only_for_target", "minimax_alt": "analysis_plus_physical_validation", "decisive": true}, "physical_methods": {"minimax": [], "minimax_alt": ["in vitro P4HA2 functional validation", "P4HA2 knockdown experiments", "combined P4HA2-knockdown and radiotherapy experiments"], "decisive": false}, "analysis_methods": {"minimax": ["Mendelian randomization"], "minimax_alt": ["single-cell transcriptomics", "spatial transcriptomics", "machine learning with SuperPC and StepCox", "Mendelian randomization", "WGCNA", "Metascape and irGSEA enrichment analysis", "Kaplan-Meier survival analysis", "chi-squared test", "Benjamini-Hochberg P-value adjustment"], "decisive": false}, "number_stated": {"minimax": false, "minimax_alt": true, "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:11d3fa4bbce2db691aae2142aebc10d9fd9317175095e50d0280ecb119807b88", "type": "sep_package", "label": "SEP v1 package for pmid:41424847"}], "activities": [{"id": "activity:conversion:pmid:41424847", "type": "conversion", "used": ["package:11d3fa4bbce2db691aae2142aebc10d9fd9317175095e50d0280ecb119807b88"], "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": "bef7b22f-c9eb-4721-b728-e9a282a3a36b", "parent_hash": "11d3fa4bbce2db691aae2142aebc10d9fd9317175095e50d0280ecb119807b88", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:41424847 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:41424847' does not resolve to a declared asset", "targets"]}