{"id":"W2600416749","doi":"10.1016/j.alter.2017.03.001","title":"Medical selection upon hiring and the applicant’s right to lie about his health status","year":2017,"lang":"en","type":"article","venue":"Alter","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Selection (genetic algorithm); Law; Political science; Psychology; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.008374713,0.0002513315,0.0003793547,0.001458121,0.006778276,0.005663232,0.001339964,0.004533783,0.01366541],"category_scores_gemma":[0.01940907,0.0002559508,0.0005199956,0.0008655062,0.01775567,0.001741514,0.003803553,0.003937327,0.002203302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007374756,"about_ca_system_score_gemma":0.01978499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1450318,"about_ca_topic_score_gemma":0.2300157,"domain_scores_codex":[0.9863377,0.003778976,0.0004901571,0.0009298204,0.004403563,0.004059831],"domain_scores_gemma":[0.9848058,0.006712429,0.002073833,0.001452331,0.003097732,0.001857809],"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":[0.0001298898,0.0001665983,0.0273255,0.0001307475,0.00002479869,0.00184479,0.02312535,0.000592315,0.001689238,0.8728307,0.01865704,0.05348301],"study_design_scores_gemma":[0.0001316482,0.000638186,0.2612667,0.002280369,0.0001026436,0.002954516,0.03770202,0.001502813,0.002326189,0.1840407,0.5068009,0.0002533146],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.209573,0.003252768,0.005800291,0.05615507,0.0004378466,0.0001848555,0.0003148945,0.00005752864,0.7242237],"genre_scores_gemma":[0.9358396,0.001015913,0.001217593,0.008380966,0.0002947827,0.00009015119,0.0001104979,0.00001695421,0.05303355],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1450318,"threshold_uncertainty_score":0.2883751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04573147001601039,"score_gpt":0.4589952240947102,"score_spread":0.4132637540786998,"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."}}