{"id":"W4220894291","doi":"10.1016/j.it.2022.03.003","title":"All is not lost: learning from 9p21 loss in cancer","year":2022,"lang":"en","type":"review","venue":"Trends in Immunology","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; Toronto General Hospital; Princess Margaret Cancer Centre; University Health Network","funders":"Genentech; Canada Research Chairs; Astellas Pharma Canada; Princess Margaret Cancer Foundation; Merck; University Health Network; Ontario Institute for Cancer Research; Roche; Novartis; University of Toronto; AbbVie; Terry Fox Research Institute; Celgene; Bayer; Bristol-Myers Squibb; AstraZeneca; Amgen; Pfizer","keywords":"Pembrolizumab; Genotype; Information and Communications Technology; Cancer; Evasion (ethics); Antibody; Immune system; Immunology; Medicine; Oncology; Immunotherapy; Internal medicine; Biology; Gene; Genetics; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003023568,0.0005015703,0.002293142,0.001213142,0.00004642809,0.00001177435,0.0003991808,0.0006273591,0.0404744],"category_scores_gemma":[0.00003642963,0.0004548342,0.0005370239,0.0011414,0.0001930944,0.00004276891,0.0002104489,0.002232228,0.0001081598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001363396,"about_ca_system_score_gemma":0.0003990409,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01011777,"about_ca_topic_score_gemma":0.001206818,"domain_scores_codex":[0.9970816,0.0004379507,0.0009613413,0.0007197862,0.000217906,0.0005813592],"domain_scores_gemma":[0.9986726,0.0002968272,0.000384989,0.0005929826,0.0000135809,0.00003900849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007584156,0.0001433882,0.0004668711,0.0006079531,0.0009455558,0.0003555351,0.0006770685,8.594624e-7,0.00001861261,0.00000707085,0.0009526845,0.995066],"study_design_scores_gemma":[0.002555006,0.0002581015,0.001944865,0.003402534,0.000388933,0.00009815862,0.00007246283,0.000003229656,0.000008670904,0.000007409121,0.9908707,0.0003899023],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008302907,0.9944788,3.956882e-7,0.0007229919,0.001081405,0.0002582068,0.0001160313,0.00004156749,0.002470294],"genre_scores_gemma":[0.0001912271,0.9891348,0.00002529836,0.0007927862,0.0001544074,0.0003241488,0.0008052973,0.00009255898,0.008479404],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9946761,"threshold_uncertainty_score":0.9997903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119142308806226,"score_gpt":0.395589634095474,"score_spread":0.2836754032148514,"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."}}