{"id":"W4323035956","doi":"10.1002/9781119790686.ch1","title":"An Introduction to AI for Non‐Experts","year":2023,"lang":"en","type":"other","venue":"AI in Clinical Medicine","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Key (lock); Machine learning; Focus (optics); Simple (philosophy); Training set; Data 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":[0.001632006,0.001081131,0.0005448426,0.001651172,0.001628197,0.004521833,0.001723932,0.003491977,0.06222083],"category_scores_gemma":[0.004395347,0.0004601348,0.0007105966,0.002391168,0.003548558,0.006490212,0.002190099,0.005092396,0.0378251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002319737,"about_ca_system_score_gemma":0.002757111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001990741,"about_ca_topic_score_gemma":0.00273549,"domain_scores_codex":[0.9985625,0.0004035216,0.00009430829,0.000181551,0.0006389738,0.0001191826],"domain_scores_gemma":[0.9972857,0.001755059,0.0001056772,0.0001961014,0.0004593152,0.0001981008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001565721,0.0000360354,0.0001301815,0.0007380905,0.000009304853,0.00009092701,0.0004304955,0.0005797094,0.0002693516,0.4242285,0.4042234,0.1692482],"study_design_scores_gemma":[0.000001767223,0.000006748329,0.00007337089,0.0002844182,0.000001242466,0.00008025124,0.00006121843,0.0001758531,0.00004376323,0.09379333,0.9054716,0.000006381072],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004601198,0.1306307,0.06044101,0.04597203,0.01054558,0.0001399752,0.000638063,0.001082841,0.7500897],"genre_scores_gemma":[0.02690362,0.2619235,0.09293056,0.0301812,0.0191963,0.0008256529,0.001228215,0.001038962,0.5657722],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06222083,"threshold_uncertainty_score":0.2081494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.136727195487171,"score_gpt":0.4542541477799338,"score_spread":0.3175269522927628,"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."}}