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pmid:40094001
The aggrephagy-related gene TUBA1B influences clinical outcomes in glioma patients by regulating the cell cycle.
Frontiers in oncology · 2025 doi:10.3389/fonc.2025.1531465
Paper
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Experiment
partial
Data
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Analysis
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Execution
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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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paper object · 10 fields
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experiment object · 8 fields
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parameters object · 0 fields
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outputs array · 1 item
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materials array · 0 items
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gaps array · 3 items
data object · 3 fields
assets array · 1 item
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structure object · 1 field
gaps array · 1 item
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axes object · 0 fields
can_run object · 3 fields
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assets array · 1 item
steps array · 1 item
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data_gaps array · 1 item
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human_critique object · 5 fields
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lineage object · 4 fields
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Complete file
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"readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40094001"]}, "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": "a21f2b6305feb3035bee3f7ddfe0a6686b01d99e1d6f5df76a371ad9ff79809b", "source_hash": "bed2a3e5e4664be32d0bb6762a921d6f69e82620681a3c47460ba244459fd3fb", "raw_response_sha256": "sha256:f0520ee18d46de294235ce44b2e5103c4e5e5bd5afa1aace0f009d38afdfac5e", "raw_response_chars": 5681}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "ac2e4e98bf4bbb67b3372b465acab037b1107311e302566ca239541be2f690fa", "source_hash": "bed2a3e5e4664be32d0bb6762a921d6f69e82620681a3c47460ba244459fd3fb", "raw_response_sha256": "sha256:06960057cfe07570a0565289c2125cac91bed90090f048340f511022867b650b", "raw_response_chars": 45404}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "fff5109309de8c4d2a996e0753bfbc13ea3925120979e500ee99643061e45d55", "source_hash": "bed2a3e5e4664be32d0bb6762a921d6f69e82620681a3c47460ba244459fd3fb", "raw_response": "{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"The paper states qualitatively that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis and that TUBA1B is an independent prognostic marker, but it provides no numerical result for this main finding.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "The paper states qualitatively that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis and that TUBA1B is an independent prognostic marker, but it provides no numerical result for this main finding.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:33:54.529718+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "110866b16fb71339eb7b8155e530103a5c724d6db38a61eec2a0a389a8ac4b10", "source_hash": "bed2a3e5e4664be32d0bb6762a921d6f69e82620681a3c47460ba244459fd3fb", "raw_response": "<think>We need answer JSON only. Need determine if numerical headline result for main finding stated in supplied text. Source mostly abstract and methods, no specific HR, AUC etc. There are numbers but not headline numerical result. Registered target: headline numerical result paper states for main finding. Need likely false because text has no quantified outcome for TUBA1B. Must leave parent_value 0, unit/evidence empty, target_result says what text states instead. Exact quotation evidence empty mandated. Need ensure maybe \"two aggrephagy subtypes\" is numerical but likely not headline numerical result? Prompt asks single numerical result replication target. Could perhaps headline result is TUBA1B? Abstract omitted specific stats. No value for main finding. Thus false.\n\nNeed JSON valid, no markdown. target_result likely concise: \"The text states that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis, but gives no numerical result for this main finding.\" Maybe quote? They request if no number, say what text states instead. Could use exact wording perhaps: \"The study demonstrates that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis, making it a potential therapeutic target.\" Evidence must be empty because says leave evidence empty. target_result can state. Ensure only object.</think>\n\n{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"The study demonstrates that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis, making it a potential therapeutic target.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "The study demonstrates that high TUBA1B expression is closely associated with glioma malignancy and poor prognosis, making it a potential therapeutic target.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:33:56.494359+00:00"}], "agreement": false, "disagreements": {"analysis_methods": {"minimax": ["normalization", "consensus clustering analysis", "immune scoring", "cell infiltration analysis", "pathway analysis", "machine learning", "multivariate Cox regression", "Gene Ontology analysis", "KEGG analysis", "Gene Set Enrichment Analysis", "Spearman analysis", "Tumor Immune Dysfunction and Exclusion analysis"], "minimax_alt": ["normalization", "consensus clustering analysis", "machine learning", "multivariate Cox regression", "nomogram modeling", "Gene Ontology (GO) analysis", "Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis", "Gene Set Enrichment Analysis (GSEA)", "TIMER", "CIBERSORT", "MCP-counter", "xCell", "Spearman analysis", "Tumor Immune Dysfunction and Exclusion (TIDE)", "Shapiro-Wilk test", "Students’ t-tests", "one-way ANOVA", "Wilcoxon test", "Kruskal-Walli test", "Kaplan-Meier method", "log-rank tests", "Cox proportional hazards regression model"], "decisive": false}, "statistical_method": {"minimax": "Kaplan-Meier method with log-rank tests and Cox proportional hazards regression", "minimax_alt": "", "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:f93e3f0ff8955ba827e5b53b64a979a7fb1959a39a2b5243464a56c1534a7b8a", "type": "sep_package", "label": "SEP v1 package for pmid:40094001"}], "activities": [{"id": "activity:conversion:pmid:40094001", "type": "conversion", "used": ["package:f93e3f0ff8955ba827e5b53b64a979a7fb1959a39a2b5243464a56c1534a7b8a"], "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": "37418d0c-c39e-4b92-878d-d85b3143ae0b", "parent_hash": "f93e3f0ff8955ba827e5b53b64a979a7fb1959a39a2b5243464a56c1534a7b8a", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40094001 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:40094001' does not resolve to a declared asset", "targets"]}