{"id":"W4413951004","doi":"10.1158/1541-7786.mcr-25-0475","title":"Cancer Genomic Alterations and Microenvironmental Features Encode Synergistic Interactions with Disease Outcomes","year":2025,"lang":"en","type":"article","venue":"Molecular Cancer Research","topic":"Ferroptosis and cancer prognosis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Research Canada; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Government of Ontario; Terry Fox Research Institute; University of Toronto; Ontario Institute for Cancer Research","keywords":"Tumor microenvironment; Immune system; Biology; Cancer; Carcinogenesis; Immunotherapy; Cancer research; Tumor progression; Computational biology; Epigenomics; Genomics; Disease; Cancer immunotherapy; Context (archaeology); Cancer immunology; Breast cancer; Bioinformatics; Immunology; Genome; Gene; DNA methylation; Medicine; Genetics; Gene expression; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009635497,0.0004076668,0.0005264708,0.001510145,0.0002623546,0.001024321,0.0002234127,0.0002268499,0.00104818],"category_scores_gemma":[0.001826491,0.0001717482,0.0004619382,0.001296842,0.0003522693,0.0003358409,0.0008007716,0.0004208287,0.0001526207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003696786,"about_ca_system_score_gemma":0.0004377144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008853898,"about_ca_topic_score_gemma":0.002435067,"domain_scores_codex":[0.999293,0.0001948818,0.00006543074,0.0002303647,0.0001339232,0.00008241001],"domain_scores_gemma":[0.9988768,0.0004492245,0.0004261684,0.0001192352,0.00005905997,0.00006951384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004431727,0.0000929091,0.8824539,0.0001662202,0.0008523006,0.0002069064,0.0001216998,0.004464047,0.08330976,0.0006611726,0.0003185472,0.02690936],"study_design_scores_gemma":[0.00001696658,0.000170865,0.9505767,0.0000272102,0.0004107248,0.0005989813,0.0002456408,0.02121869,0.02133157,0.003597036,0.001778462,0.00002728855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841576,0.0008286081,0.01106139,0.0001800652,0.000007572899,0.00002543397,0.002834446,0.0001491842,0.0007556451],"genre_scores_gemma":[0.994768,0.0001212936,0.003943325,0.00003837832,0.000006264681,0.00001286119,0.0009984409,0.00001456772,0.00009679015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001510145,"threshold_uncertainty_score":0.00509584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02550409308856488,"score_gpt":0.3824373261287921,"score_spread":0.3569332330402272,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}