{"id":"W3179030148","doi":"10.1158/1538-7445.am2021-208","title":"Abstract 208: Development of Evidence Statement curation algorithms to aid cancer variant interpretation","year":2021,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Spinal Cord Injury BC","funders":"","keywords":"Data curation; Statement (logic); Computer science; Interpretation (philosophy); Clinical trial; Evidence-based medicine; Prioritization; Data science; Medicine; Alternative medicine; Pathology; Management science; Political science","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":[0.07191938,0.002266494,0.002145152,0.01641013,0.002213022,0.01185176,0.00502512,0.003614323,0.03209368],"category_scores_gemma":[0.3441834,0.001768836,0.005210964,0.007758674,0.001510839,0.005634802,0.007123684,0.005285258,0.0150607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004078274,"about_ca_system_score_gemma":0.01917207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004117173,"about_ca_topic_score_gemma":0.007091374,"domain_scores_codex":[0.9445368,0.02653389,0.014498,0.00295391,0.01092383,0.0005535136],"domain_scores_gemma":[0.719056,0.1791599,0.01636028,0.01488823,0.0677183,0.002817351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006033392,0.0002559166,0.0039333,0.01169165,0.000808804,0.0005975984,0.001289855,0.01923294,0.002343829,0.03876983,0.2416353,0.6788377],"study_design_scores_gemma":[0.001221617,0.0003950206,0.003776241,0.0217527,0.001681171,0.001160227,0.001056761,0.2153493,0.01968346,0.1765769,0.5569518,0.000394782],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003688652,0.002894803,0.9195938,0.01328355,0.00120748,0.01365793,0.01715508,0.01521216,0.01330667],"genre_scores_gemma":[0.007651763,0.0005871783,0.9815133,0.0007475397,0.00018166,0.002385233,0.005107282,0.0005826805,0.001243402],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07191938,"threshold_uncertainty_score":0.3803506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1481163339661219,"score_gpt":0.4561982996584764,"score_spread":0.3080819656923546,"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."}}