{"id":"W7001624361","doi":"","title":"Les opÃ©rations scrutÃ©es sous l'angle de l'intÃ©rÃªt public par les organismes de rÃ©glementation des valeurs mobiliÃ¨res : entre efficience et duplicitÃ©","year":2008,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Pilotage; Criminal liability; Decantation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00003793538,0.0004134405,0.000315583,0.00005229309,0.0005558114,0.00008536918,0.0004512752,0.0001544665,0.0005395041],"category_scores_gemma":[0.00005440697,0.0004249561,0.00006628544,0.0001007426,0.0005000199,0.00005404307,0.0002671089,0.0002694215,2.986929e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004064657,"about_ca_system_score_gemma":0.003176047,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009555059,"about_ca_topic_score_gemma":0.0891045,"domain_scores_codex":[0.997518,0.0002405846,0.0004540821,0.0003781481,0.0008411412,0.000568025],"domain_scores_gemma":[0.9987606,0.000178897,0.000406687,0.0003203611,0.00000390991,0.0003294989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002469519,0.0003914697,0.5328689,0.002061984,0.0007847709,0.0001166342,0.003088934,0.008228897,0.227957,0.08277899,0.01671928,0.1247562],"study_design_scores_gemma":[0.001346204,0.0007886632,0.1601741,0.0007118613,0.0002129705,0.0002012319,0.01913848,0.01540074,0.3733826,0.0008517544,0.42604,0.001751326],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6393151,0.003055618,0.01383461,0.004565198,0.0002220379,0.0006194771,0.0009559665,0.00003182801,0.3374001],"genre_scores_gemma":[0.9370845,0.003329934,0.01509906,0.001200278,0.0001339127,0.000028228,0.0002392386,0.0001065078,0.04277834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4093207,"threshold_uncertainty_score":0.9998202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005149604060940892,"score_gpt":0.1814009745273046,"score_spread":0.1762513704663637,"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."}}