{"id":"W1995453026","doi":"10.1002/humu.1113","title":"Variable expressivity and mutation databases: The androgen receptor gene mutations database","year":2001,"lang":"en","type":"article","venue":"Human Mutation","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; John Abbott College","funders":"","keywords":"Biology; Database; Genetics; Gene; Mutation; Computer 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":[0.004277566,0.0009356037,0.001048308,0.01300922,0.0006727076,0.002690277,0.002341793,0.002074838,0.008556248],"category_scores_gemma":[0.0179388,0.0005500868,0.0006144854,0.01037016,0.0004708504,0.002900865,0.002068972,0.001294101,0.008156013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008081148,"about_ca_system_score_gemma":0.002180121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004089563,"about_ca_topic_score_gemma":0.005223965,"domain_scores_codex":[0.9974692,0.0003054046,0.0009965661,0.000284721,0.000832351,0.0001117375],"domain_scores_gemma":[0.9885846,0.003697331,0.002409431,0.001917376,0.002222147,0.001169077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002238438,0.0006431346,0.06092237,0.006706021,0.0006250535,0.00396209,0.00121099,0.007861707,0.02635727,0.03322285,0.4432273,0.4130229],"study_design_scores_gemma":[0.0003543421,0.000228277,0.04900439,0.0009952242,0.0003771197,0.005395698,0.0004490899,0.01221055,0.01734939,0.02034847,0.8930553,0.0002321728],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05486267,0.01027915,0.05327614,0.003325037,0.0002942293,0.0007779545,0.8288984,0.02601796,0.02226846],"genre_scores_gemma":[0.04630886,0.004053818,0.04333828,0.0006930378,0.00009802688,0.0003624593,0.8991757,0.001614421,0.004355483],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01300922,"threshold_uncertainty_score":0.02862352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02190913411489236,"score_gpt":0.2802097073718418,"score_spread":0.2583005732569494,"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."}}