{"id":"W26580578","doi":"10.1021/acs.jnatprod.5b00574","title":"Séduire : tirer à l’écart, corrompre","year":2004,"lang":"en","type":"article","venue":"Liberté","topic":"Health, Medicine and Society","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Norges Forskningsråd","keywords":"Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004555433,0.0001325105,0.0002523938,0.00003063266,0.0006431247,0.00000391602,0.0001509741,0.0004893577,0.0009723582],"category_scores_gemma":[0.0001614526,0.0001058413,0.00007834557,0.0001922012,0.00005298489,0.0001026935,0.00005980095,0.001212778,0.002453251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001870321,"about_ca_system_score_gemma":0.0007905965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00087758,"about_ca_topic_score_gemma":0.0002270065,"domain_scores_codex":[0.998316,0.0002083493,0.0003798669,0.0002403473,0.0002349877,0.00062043],"domain_scores_gemma":[0.9988965,0.0002722759,0.00008673847,0.0003740162,0.00007293005,0.0002975324],"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":[0.00008844891,0.0003931634,0.04749073,0.001336471,0.00008583934,0.0001452797,0.2249377,0.00002083592,0.0007431195,0.06739557,0.62524,0.03212278],"study_design_scores_gemma":[0.00194898,0.0001068718,0.03188612,0.0003349386,0.00001945249,0.000004297495,0.009864826,0.0000142259,0.00004391217,0.002528519,0.9530623,0.0001855401],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6019506,0.0003650623,0.0002965697,0.02606105,0.002238988,0.0008611735,0.00001343179,0.0003982893,0.3678148],"genre_scores_gemma":[0.8887604,0.0001529999,0.0007836068,0.05976196,0.001324,0.0001086317,0.00002992646,0.00005034115,0.04902809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3278223,"threshold_uncertainty_score":0.9999409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04309242996115696,"score_gpt":0.3849966687401459,"score_spread":0.3419042387789889,"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."}}