{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002919122,0.0007638144,0.002342701,0.001824563,0.000320389,0.002118493,0.001385526,0.001756735,0.00351859],"category_scores_gemma":[0.003955052,0.0002732039,0.001071446,0.00112159,0.001119868,0.003396671,0.0009938887,0.003683012,0.002323223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304695,"about_ca_system_score_gemma":0.001816261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001480902,"about_ca_topic_score_gemma":0.002327013,"domain_scores_codex":[0.999437,0.0001865322,0.00007702366,0.00009656316,0.0001478678,0.00005507058],"domain_scores_gemma":[0.9984976,0.0009521861,0.0001331113,0.00004611001,0.0002835976,0.00008732436],"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":[0.0000982795,0.00003720871,0.0005732207,0.009957469,0.000239602,0.0002584019,0.0000618851,0.000651481,0.0005856128,0.0161069,0.04287937,0.9285504],"study_design_scores_gemma":[0.00004268913,0.0001298342,0.001317092,0.0095676,0.0002697411,0.002112715,0.0001783448,0.0003402398,0.000404619,0.02012764,0.9654566,0.00005287722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001115741,0.9930332,0.0005047428,0.004925575,0.0005171414,0.000007530998,0.00003525471,0.00001418527,0.0008507736],"genre_scores_gemma":[0.002181113,0.9936081,0.0007182134,0.001976104,0.0008023842,0.00001927299,0.00006464186,0.00000731976,0.0006228095],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00351859,"threshold_uncertainty_score":0.01543796,"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."}}