{"id":"W6989884036","doi":"","title":"Chien blanc, Anaïs Barbeau-Lavalette (Québec)","year":2023,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Set (abstract data type); Identification (biology); Natural (archaeology); Selection (genetic algorithm); 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":[0.001962316,0.0008848251,0.0005429669,0.001636029,0.01136449,0.005314045,0.001063119,0.002010379,0.1542292],"category_scores_gemma":[0.005354888,0.0004374493,0.0003873147,0.001655596,0.001297186,0.001623187,0.001662979,0.002347504,0.02735961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03275001,"about_ca_system_score_gemma":0.05159673,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9638155,"about_ca_topic_score_gemma":0.9824558,"domain_scores_codex":[0.998481,0.0002083473,0.00004897278,0.0002973347,0.0005743077,0.0003900736],"domain_scores_gemma":[0.9952781,0.0002455271,0.0001289818,0.00009054472,0.002839054,0.001417737],"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":[0.00003786424,0.00002333825,0.00226274,0.00009794568,0.00001050036,0.0001965779,0.0008811808,0.0001032453,0.00020488,0.006242626,0.9239706,0.0659685],"study_design_scores_gemma":[0.000006125451,0.000005969522,0.004321971,0.0001026294,0.000008027388,0.00009196115,0.00155223,0.00007663143,0.0001510876,0.0003767384,0.9932871,0.00001943937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01340885,0.1177992,0.003504557,0.3696879,0.03353151,0.0003428572,0.006432136,0.00126314,0.4540299],"genre_scores_gemma":[0.02975061,0.01272078,0.001196021,0.0100299,0.0007227896,0.00005572968,0.0005559292,0.0002079651,0.9447602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1542292,"threshold_uncertainty_score":0.5159482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005855538131770809,"score_gpt":0.1581760731489102,"score_spread":0.1523205350171394,"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."}}