{"id":"W1992539804","doi":"10.1136/jmg.2005.032441","title":"MELPREDICT: a logistic regression model to estimate CDKN2A carrier probability","year":2005,"lang":"en","type":"article","venue":"Journal of Medical Genetics","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; American Skin Association; National Institutes of Health; Dermatology Foundation","keywords":"CDKN2A; Proband; Logistic regression; Germline mutation; Confidence interval; Statistics; Receiver operating characteristic; Penetrance; Mutation; Medicine; Genetics; Internal medicine; Cancer; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007668214,0.001679194,0.001463695,0.00222584,0.0004954559,0.001326828,0.002576986,0.001285376,0.005707174],"category_scores_gemma":[0.01765669,0.0007299411,0.001943488,0.001138683,0.0004338103,0.001082144,0.001167627,0.002304563,0.001730577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001062696,"about_ca_system_score_gemma":0.001322802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01353251,"about_ca_topic_score_gemma":0.007861194,"domain_scores_codex":[0.9972519,0.001857047,0.0001195476,0.0004627554,0.0001667698,0.0001418901],"domain_scores_gemma":[0.9856126,0.01228592,0.0007851243,0.0004306046,0.0006473999,0.0002383426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002971997,0.000670124,0.3231021,0.0003330624,0.001754952,0.001164678,0.0002839985,0.523244,0.0007702635,0.005090886,0.02197214,0.1186417],"study_design_scores_gemma":[0.00006116,0.0001075727,0.004411378,0.000020165,0.00007324124,0.0001405766,0.00002946364,0.9922366,0.0001229807,0.00184275,0.0009376825,0.00001652737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5199199,0.002613252,0.4452457,0.005458647,0.0004759482,0.0005846915,0.01547383,0.007261865,0.002966126],"genre_scores_gemma":[0.8986118,0.0007167011,0.08656,0.0003807489,0.0002973596,0.0005358653,0.008466044,0.0002934693,0.004137905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01353251,"threshold_uncertainty_score":0.04055387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05122499361929941,"score_gpt":0.3610103133530479,"score_spread":0.3097853197337485,"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."}}