{"id":"W4248204465","doi":"10.1007/s00266-002-4315-5","title":"Patient Selection","year":2002,"lang":"en","type":"article","venue":"Aesthetic Plastic Surgery","topic":"Healthcare Systems and Challenges","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Otorhinolaryngology; Plastic surgery; Selection (genetic algorithm); General surgery; Surgery; Artificial intelligence","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":[0.00108834,0.0007414494,0.0009616864,0.002198919,0.001289179,0.001152868,0.0007364562,0.0006696318,0.1942416],"category_scores_gemma":[0.00369649,0.0002431385,0.001014703,0.001002841,0.0002636598,0.0005587187,0.001283056,0.0008013861,0.04595227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000677774,"about_ca_system_score_gemma":0.002063439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00063437,"about_ca_topic_score_gemma":0.001586127,"domain_scores_codex":[0.9990488,0.0001939018,0.0001342796,0.000176388,0.0002253597,0.0002213598],"domain_scores_gemma":[0.9990977,0.0001291601,0.00007715451,0.000109942,0.0001856935,0.0004003126],"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":[0.004872572,0.002951103,0.1028998,0.001370044,0.0001257607,0.01337618,0.0007662427,0.000873186,0.005817161,0.005452172,0.2690607,0.5924351],"study_design_scores_gemma":[0.001641834,0.003939514,0.09490892,0.001935199,0.0002088855,0.02910508,0.001127172,0.001814573,0.003194299,0.005128939,0.8568704,0.0001251852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3296681,0.0103201,0.02793317,0.01202621,0.007526096,0.0501185,0.03652398,0.001062547,0.5248213],"genre_scores_gemma":[0.5146285,0.009849382,0.03018088,0.02160792,0.006275123,0.0489032,0.03801166,0.001141122,0.3294022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1942416,"threshold_uncertainty_score":0.6498029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077995403269366,"score_gpt":0.3444850597616542,"score_spread":0.2366855194347177,"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."}}