{"id":"W4298326506","doi":"10.1093/fampra/cmac104","title":"An introduction to machine learning for classification and prediction","year":2022,"lang":"en","type":"article","venue":"Family Practice","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Western University; University of Calgary","funders":"University of Calgary","keywords":"Machine learning; Interpretability; Artificial intelligence; Computer science; Hyperparameter; Support vector machine; Predictive power; Decision tree; Artificial neural network; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001703812,0.00008355359,0.00008144671,0.0001367142,0.0007660186,0.0001345857,0.0002871003,0.00002833832,0.000007976842],"category_scores_gemma":[0.001317128,0.00009675085,0.00001518118,0.0003711508,0.000008634473,0.001062384,0.0001625426,0.0004510077,0.000005973028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001235832,"about_ca_system_score_gemma":0.0000525064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001663089,"about_ca_topic_score_gemma":0.000004056455,"domain_scores_codex":[0.9981902,0.0006651824,0.000182235,0.0005093246,0.0002824714,0.000170609],"domain_scores_gemma":[0.9988445,0.0003540562,0.0001624212,0.0003905359,0.000149664,0.00009879628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008566557,0.0005718857,0.02849681,0.0001672775,0.00005680838,0.000009520483,0.01288156,0.1486087,0.04364423,0.1682238,0.02283426,0.5736485],"study_design_scores_gemma":[0.0001297645,0.000693883,0.02086725,9.07083e-7,0.0000067278,0.00003781909,0.0005031391,0.5024948,0.00001059396,0.0001180801,0.47507,0.00006706689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03282051,0.0001891186,0.8828069,0.08110396,0.001398529,0.0007305869,0.00001259619,0.0004862582,0.0004515763],"genre_scores_gemma":[0.8847983,0.00001748476,0.1112147,0.002560534,0.0006379557,0.0003386285,0.00008780186,0.00001970465,0.0003248674],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8519778,"threshold_uncertainty_score":0.5891674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0365632557687345,"score_gpt":0.3303990513829546,"score_spread":0.2938357956142201,"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."}}