{"id":"W4313136842","doi":"10.7202/1084695ar","title":"Apprendre du passé, façonner l’avenir : 50 ans de langues officielles au Canada","year":2021,"lang":"fr","type":"article","venue":"Minorités linguistiques et société","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002423585,0.0002162441,0.0002968676,0.001217921,0.0200118,0.00605336,0.0008390145,0.001058393,0.004162819],"category_scores_gemma":[0.003336717,0.0002678595,0.0002236308,0.00173944,0.01016358,0.001879938,0.003299149,0.00320037,0.0003574242],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08280259,"about_ca_system_score_gemma":0.09452731,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9924065,"about_ca_topic_score_gemma":0.9975212,"domain_scores_codex":[0.9967149,0.0004061443,0.00004292245,0.0002263018,0.000827481,0.001782253],"domain_scores_gemma":[0.9964316,0.0002738304,0.0002042561,0.00009906865,0.001401033,0.001590149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002133548,0.00007180458,0.05141233,0.00009021992,0.00001999044,0.000790592,0.7859148,0.0002197455,0.002117907,0.09005274,0.01742172,0.05167473],"study_design_scores_gemma":[0.00001273405,0.00006580243,0.2026065,0.0001829222,0.00002329014,0.0001682572,0.3843797,0.0002045089,0.0007383212,0.001904884,0.4096168,0.00009626154],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8742781,0.002463457,0.0004400212,0.01585974,0.0001630011,0.00004774237,0.0003068974,0.00002275053,0.1064183],"genre_scores_gemma":[0.9649168,0.000730179,0.0001828573,0.0009756871,0.00001695875,0.00001057786,0.00006639298,0.00002043873,0.03308012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9171974,"threshold_uncertainty_score":0.6007777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01504550475221332,"score_gpt":0.2756746045366358,"score_spread":0.2606290997844225,"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."}}