{"id":"W4312000342","doi":"10.3390/healthcare10122493","title":"Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment","year":2022,"lang":"en","type":"article","venue":"Healthcare","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":324,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Health care; Population ageing; Population; Artificial intelligence; Medicine; Gerontology; Computer science; Economics; Environmental health; Economic growth","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":[0.01593643,0.0008401825,0.001623104,0.001973549,0.0006741738,0.005154605,0.001719757,0.002677093,0.008788434],"category_scores_gemma":[0.06165451,0.0005749629,0.001779505,0.00210503,0.004793806,0.005645816,0.002513434,0.004217031,0.0003481166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007565485,"about_ca_system_score_gemma":0.005119014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004892829,"about_ca_topic_score_gemma":0.002685874,"domain_scores_codex":[0.9731151,0.02109316,0.0007764392,0.001371998,0.002748491,0.000894894],"domain_scores_gemma":[0.9123251,0.07931741,0.003720226,0.001737518,0.002106903,0.0007928121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009923221,0.0002798681,0.00891545,0.002346849,0.000692741,0.0001903899,0.0003174544,0.1956607,0.0004075215,0.7095279,0.003509344,0.07715959],"study_design_scores_gemma":[0.0005910612,0.0006916436,0.008827564,0.002577014,0.0006745678,0.0002705753,0.0006592051,0.2044063,0.001031666,0.7610726,0.01908992,0.0001078554],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2160905,0.05401426,0.4885031,0.1126965,0.001597633,0.002397989,0.002356079,0.000268218,0.1220757],"genre_scores_gemma":[0.9451513,0.008455479,0.03967203,0.002286386,0.0003940395,0.001194191,0.0002174508,0.00003787564,0.002591246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01593643,"threshold_uncertainty_score":0.08428091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2098978576872646,"score_gpt":0.4315680880884908,"score_spread":0.2216702304012262,"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."}}