{"id":"W4406577567","doi":"10.1016/s1544-8800(10)70065-8","title":"10.1016/s1544-8800(10)70065-8","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Framingham Risk Score; Calcium; Algorithm; Computer science; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001379738,0.003589688,0.002113297,0.003462242,0.002289638,0.004151845,0.00424078,0.005733375,0.9902439],"category_scores_gemma":[0.002180383,0.001146972,0.001893538,0.003364405,0.002108959,0.006263966,0.003768679,0.003234881,0.9939151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126614,"about_ca_system_score_gemma":0.001164099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003730322,"about_ca_topic_score_gemma":0.003048423,"domain_scores_codex":[0.999149,0.00005924855,0.00006888254,0.0003176288,0.0002392389,0.0001660015],"domain_scores_gemma":[0.9969816,0.0008628822,0.0001826469,0.0004485715,0.0005565811,0.0009677559],"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":[0.0003980489,0.0002349175,0.0006810545,0.0005651791,0.00004333996,0.000225757,0.00007423724,0.0006052088,0.002269991,0.004821183,0.3427772,0.6473039],"study_design_scores_gemma":[0.00008773417,0.0001375667,0.0007462744,0.0003323324,0.00001834237,0.000335629,0.00009514558,0.0004789345,0.0006305248,0.0009514024,0.9961479,0.00003834076],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000471875,0.0004869455,0.001678073,0.0004319845,0.0003997589,0.0001495505,0.001480917,0.002101724,0.9927992],"genre_scores_gemma":[0.0005416337,0.0002078953,0.0007109054,0.0002157769,0.00008640833,0.0000790518,0.0006841673,0.0002932815,0.9971809],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.009756148,"threshold_uncertainty_score":0.01391596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002722198243897024,"score_gpt":0.1803409691307968,"score_spread":0.1776187708868998,"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."}}