{"id":"W7039042764","doi":"","title":"L’avenir de la formation en gérontologie au Canada et autres notes distinctes","year":2009,"lang":"fr","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Subject (documents); Context (archaeology); Period (music)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003752737,0.0002691006,0.0002768706,0.002821343,0.0002975227,0.0002223231,0.0006732185,0.0001869773,0.00006467142],"category_scores_gemma":[0.0003855918,0.0003003724,0.0001669513,0.004569837,0.0001114608,0.00152111,0.0001737054,0.0003191126,0.00001867555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002615953,"about_ca_system_score_gemma":0.005508945,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9413283,"about_ca_topic_score_gemma":0.9696457,"domain_scores_codex":[0.9977516,0.0007873618,0.0002034848,0.0003987295,0.0002821289,0.0005766801],"domain_scores_gemma":[0.9984486,0.0007351432,0.0001661626,0.000325381,0.000154676,0.0001700909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006310745,0.0006688932,0.002164871,0.0002264216,0.0002275001,0.00123559,0.02088477,0.001691134,0.00003657187,0.09911209,0.003254117,0.8704349],"study_design_scores_gemma":[0.0005326738,0.0001121576,0.003591938,0.0001402076,0.0001307931,0.00004494694,0.0005752673,0.0421337,0.0005942672,0.00002676613,0.951741,0.0003763131],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03363245,0.00002321605,0.1813568,0.01975572,0.0004708852,0.0003527846,0.0001291068,0.0003073256,0.7639717],"genre_scores_gemma":[0.9591897,0.03289314,0.006633351,0.00075147,0.0001183292,0.000001020434,0.00004393532,0.00001040452,0.0003586789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9484869,"threshold_uncertainty_score":0.9999449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0213647481062326,"score_gpt":0.2434734423979475,"score_spread":0.2221086942917149,"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."}}