{"id":"W4387479209","doi":"10.1515/dx-2023-0108","title":"Tumor heterogeneity: how could we use it to achieve better clinical outcomes?","year":2023,"lang":"en","type":"review","venue":"Diagnosis","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Tumor heterogeneity; Computer science; Medicine; Internal medicine; Cancer","routes":{"ca_aff":true,"ca_fund":false,"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"],"consensus_categories":[],"category_scores_codex":[0.0003964122,0.0007135603,0.001827953,0.0001588958,0.00009383881,0.0002635444,0.0007178648,0.0006959941,0.00002690817],"category_scores_gemma":[0.001652807,0.0006324174,0.001598419,0.0002685709,0.00008376153,0.000005230143,0.0008673647,0.0004271723,0.0006141768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007443244,"about_ca_system_score_gemma":0.000281806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005125683,"about_ca_topic_score_gemma":0.0004537991,"domain_scores_codex":[0.9967977,0.0002070073,0.0008885868,0.001223304,0.0002641719,0.0006192118],"domain_scores_gemma":[0.9968131,0.0009332331,0.000382187,0.001326597,0.0001067171,0.0004382309],"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":[0.00002194398,0.0002335053,0.01250169,0.001932074,0.001189334,0.0001211865,0.00001036484,0.000003780408,0.000002393047,0.00001549018,0.4808958,0.5030724],"study_design_scores_gemma":[0.0002429098,0.0003588795,0.0005000337,0.001481779,0.0007110978,0.00000958069,0.000005082968,5.813638e-7,0.00003451466,0.000008845576,0.9959114,0.0007353636],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003957537,0.9844102,0.00007513423,0.004749417,0.002212468,0.001664578,0.002832146,0.00005792799,0.00004055253],"genre_scores_gemma":[0.00005261531,0.9862034,0.0003869061,0.008742287,0.001360914,0.001342812,0.0009429402,0.0002294659,0.0007386327],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5150155,"threshold_uncertainty_score":0.9996127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1722561318235344,"score_gpt":0.4195446111705146,"score_spread":0.2472884793469802,"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."}}