{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002822256,0.0001101694,0.0002837594,0.00003206135,0.001913065,0.00003961898,0.000242744,0.0001359748,0.002542708],"category_scores_gemma":[0.002954746,0.00006373463,0.0000312472,0.00004470686,0.0001652317,0.000140639,0.0002207001,0.0007864108,0.000511853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009675368,"about_ca_system_score_gemma":0.0003647373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008556317,"about_ca_topic_score_gemma":0.004257832,"domain_scores_codex":[0.9977432,0.0005737725,0.0003921642,0.0002826893,0.000424022,0.000584159],"domain_scores_gemma":[0.9974504,0.001155078,0.0002334886,0.0004921932,0.00006270117,0.0006061284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001306909,0.0002751586,0.166583,0.00127127,0.0001449463,0.00001711301,0.03406351,0.000001311459,0.00009803091,0.07813117,0.4280488,0.2900588],"study_design_scores_gemma":[0.001302319,0.00008150542,0.04298043,0.0002142605,0.00001517229,0.000002241913,0.0004573034,0.0002572359,0.00002253333,0.001446483,0.9531286,0.00009194541],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5133196,0.000360817,0.0009372194,0.4668828,0.001021582,0.001365428,0.000005973349,0.00008003231,0.01602664],"genre_scores_gemma":[0.969766,0.0005374535,0.0003154563,0.02542024,0.001304268,0.0002178863,0.000003683138,0.00001599844,0.002418979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5250797,"threshold_uncertainty_score":0.9993863,"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."}}