Development of the TP53 mutation associated hypopharyngeal squamous cell carcinoma prognostic model through bulk multi-omics sequencing and single-cell sequencing.

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["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:39341197"]}, "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": "8aa8f464b8f6fb3c0f588b5e36feee73d8b8948e29fb8262ddb89b6d48140b42", "source_hash": "60c5f57c19c7a54bc9929ee4e6e2aa3a75a13a8007b047a7c29ef41b486a9566", "raw_response_sha256": "sha256:480af8b215a1a308c0b83ddb20ac1db95593a8a69d18796a7b19fe9fb4a9bf47", "raw_response_chars": 5405}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "a914a48fd907c6b10e347f8c89bdf373ca23d3baacbd3cf336f80d8994eddce1", "source_hash": "60c5f57c19c7a54bc9929ee4e6e2aa3a75a13a8007b047a7c29ef41b486a9566", "raw_response_sha256": "sha256:3adc276f76735d32227e23f42cf879c0dae1a9cb85621d1788a92e585925ca7d", "raw_response_chars": 68248}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "4fc1107f53a146827b4ffed7bdb5895f248f103e25bb6592903aa5b77d4f6519", "source_hash": "60c5f57c19c7a54bc9929ee4e6e2aa3a75a13a8007b047a7c29ef41b486a9566", "raw_response": "{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"The paper states that the TP53 mutation-associated HPSCC prognostic model was constructed via POLD2 and POLR2G, with high-risk group samples exhibiting poorer prognosis, but it does not state a headline numerical result for the registered target.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "The paper states that the TP53 mutation-associated HPSCC prognostic model was constructed via POLD2 and POLR2G, with high-risk group samples exhibiting poorer prognosis, but it does not state a headline numerical result for the registered target.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:18:34.363212+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "1b2385b8a478be917944b22f2f9cdffd899739f55d33a1d36f8debb50af26115", "source_hash": "60c5f57c19c7a54bc9929ee4e6e2aa3a75a13a8007b047a7c29ef41b486a9566", "raw_response": "<think>We need solve extraction task. We have source text abstract etc no headline numerical result for main finding. Need JSON object with false parent 0 unit empty evidence empty target_result describing text states instead. Need ensure no numerical result attached to main model. We should carefully examine source for perhaps \"29 immune-related gene sets\" but not main finding. Registered target headline numerical result paper states for main finding. Paper text no numerical model performance, no C-index/AUC etc. It gives \"29 immune-related gene sets\", \"KNN 0.3 resolution\", etc irrelevant. Need not choose those. Need report no number. target_result likely text states prognostic model of TP53 mutation constructed via POLD2 and POLR2G; high-risk group poorer prognosis; correlations with lymphatic metastasis and immune scores; single-cell higher expressions in epithelial cells and macrophages. We need concise describe no headline numerical result; text states qualitative findings.\n\nNeed output strict JSON no markdown. Fields exact. Could use evidence empty \"\". target_result \"No headline numerical result is stated for the main finding. The text instead reports that the TP53 mutation-associated HPSCC prognostic model was constructed via POLD2 and POLR2G, that high-risk group samples had poorer prognosis, and that risk scores correlated with lymphatic metastasis and immune scores.\" Should not perhaps quote as no evidence requirement if number_stated false evidence empty. Unit empty.\n\nWe should consider user asks \"find the single numerical result that a replication of the registered target has to reproduce\". No number. We should accurately say no headline numerical result. parent_value zero as instructed. no invention.\n\nNeed ensure target_result not introduce numeric values not related? It can state numbers 29? Not needed. Maybe \"The paper reports qualitative findings only: ...\" Good.\n\nPotential interpretation headline numerical result may be 2 key genes? But user says \"the value the paper itself states for the registered target, not a value you calculated...\" Main finding model via POLD2 and POLR2G, two key genes. \"two key genes\" is numeric but not headline numerical result the paper itself states for main finding? We should examine what benchmark likely wants. Often these tasks are extract numerical results from papers with target registered. If no headline numerical result in source text e.g abstract lacks metrics, answer false. We must not infer \"two key genes\" headline result because main finding is prognostic model and no performance outcome. Need no number.\n\nCould there be result metric hidden in exact wording \"a total of 29 immune-related gene sets\"? That's a numerical result for immune score analysis, but not main finding. No.\n\nMaybe \"TP53 mutation associated hypopharyngeal...\" no actual numbers. Fine.\n\nWe can finish JSON concise.</think>\n\n{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"No headline numerical result is stated for the main finding. The paper instead reports that the TP53 mutation-associated HPSCC prognostic model was constructed via POLD2 and POLR2G, that high-risk group samples exhibited poorer prognosis, and that risk scores correlated with lymphatic metastasis and immune scores.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "No headline numerical result is stated for the main finding. The paper instead reports that the TP53 mutation-associated HPSCC prognostic model was constructed via POLD2 and POLR2G, that high-risk group samples exhibited poorer prognosis, and that risk scores correlated with lymphatic metastasis and immune scores.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:18:43.015261+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "unclear", "minimax_alt": "Initially, two key genes, POLD2 and POLR2G, were identified and utilized to construct the prognostic model.", "decisive": false}, "analysis_methods": {"minimax": ["Gene Set Enrichment Analysis (GSEA)", "univariate Cox analysis", "multivariate Cox analysis", "LASSO analysis", "ROC curve analysis", "Gene Ontology analysis", "GSVA", "single-cell RNA sequencing analysis using Seurat", "Harmony integration", "unbiased K-Nearest Neighbor (KNN) clustering", "SingleR cell annotation", "AddModuleScore"], "minimax_alt": ["GSEA", "univariate Cox analysis", "multivariate Cox analysis", "LASSO analysis", "ROC curve validation of OS and RFS results", "risk-score-based stratification into high-risk and low-risk groups"], "decisive": false}, "statistical_method": {"minimax": "", "minimax_alt": "GSEA, univariate and multivariate Cox analyses, and LASSO analysis", "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:dd8a3aef1358a8cc03f70433c7da7c34ff14ea972cf3ea439d5ab6d12cccc243", "type": "sep_package", "label": "SEP v1 package for pmid:39341197"}], "activities": [{"id": "activity:conversion:pmid:39341197", "type": "conversion", "used": ["package:dd8a3aef1358a8cc03f70433c7da7c34ff14ea972cf3ea439d5ab6d12cccc243"], "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": "3a866b12-43a2-43bd-97bc-09db969ee245", "parent_hash": "dd8a3aef1358a8cc03f70433c7da7c34ff14ea972cf3ea439d5ab6d12cccc243", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:39341197 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:39341197' does not resolve to a declared asset", "targets"]}