{"id":"W7048922708","doi":"","title":"Noir·es sous surveillance à Montréal","year":2022,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Advanced Electrical Measurement Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Identification (biology); Context (archaeology); Set (abstract data type); Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009283485,0.001839742,0.0007149793,0.00225303,0.003869413,0.003962987,0.001120128,0.001351587,0.1067394],"category_scores_gemma":[0.002156728,0.0005026977,0.0009181494,0.001667748,0.0009162636,0.000800754,0.001483955,0.002400469,0.01274406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01513262,"about_ca_system_score_gemma":0.01792794,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7981444,"about_ca_topic_score_gemma":0.8307189,"domain_scores_codex":[0.9984078,0.0002021929,0.00005819862,0.0003349355,0.0006020474,0.0003949389],"domain_scores_gemma":[0.998125,0.0002204546,0.0001569351,0.00009503795,0.0007794895,0.0006230586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001472388,0.0005451129,0.07842995,0.0009654053,0.000652169,0.007605626,0.001655325,0.004569251,0.01337211,0.0546736,0.3727754,0.4632837],"study_design_scores_gemma":[0.0001052394,0.0001901392,0.1057468,0.0002564696,0.0000753363,0.0009572836,0.0007293858,0.001516196,0.002485816,0.0007412826,0.8871193,0.00007675692],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1310037,0.02290602,0.008541621,0.0219673,0.006717573,0.0006762133,0.0245544,0.003434186,0.7801989],"genre_scores_gemma":[0.1849277,0.00594004,0.004610309,0.001483848,0.001087988,0.0001794649,0.004148277,0.0002911139,0.7973312],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2018556,"threshold_uncertainty_score":0.4060887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005326819742428132,"score_gpt":0.1558441828894995,"score_spread":0.1505173631470714,"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."}}