{"id":"W1687893991","doi":"10.22329/gljuh.v3i1.8827","title":"Muzzles and Mixed Messages: Issues Between Science and the Federal Government In Canada’s Past and Present","year":2024,"lang":"en","type":"article","venue":"˜The œGreat Lakes journal of undergraduate history.","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; University of King's College","funders":"","keywords":"Government (linguistics); Political science; Public administration; Public relations; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001829263,0.0001072223,0.0002327287,0.0001714678,0.001069962,0.000541457,0.0002782424,0.00003236615,0.00001693763],"category_scores_gemma":[0.0000795251,0.00007650187,0.00003831183,0.0001821881,0.003431082,0.0003347716,0.00006174355,0.0002616434,7.514103e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006150155,"about_ca_system_score_gemma":0.004002573,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9363887,"about_ca_topic_score_gemma":0.9985548,"domain_scores_codex":[0.9980205,0.0002429914,0.0002734917,0.0001801629,0.001024645,0.0002581746],"domain_scores_gemma":[0.9991595,0.0003156552,0.0001310409,0.0001061203,0.00007765667,0.000210058],"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":[0.0002602256,0.00005349429,0.04185914,0.0002985607,0.0004027008,0.0008300448,0.1200733,0.0000330768,0.0001494597,0.07965627,0.6227983,0.1335855],"study_design_scores_gemma":[0.0003944337,0.00002430499,0.01257194,0.00008627085,0.00005734709,0.00004105575,0.004392238,0.0000436653,0.000001353058,0.002141493,0.9801395,0.00010641],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6207122,0.1665472,0.00002276031,0.1916667,0.002488228,0.0005285501,0.00003616217,0.00002171842,0.01797646],"genre_scores_gemma":[0.9878088,0.003860114,0.00001138252,0.0001441972,0.000277401,0.000002695134,1.545092e-7,0.000008171708,0.007887043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670967,"threshold_uncertainty_score":0.999281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524433082071107,"score_gpt":0.2289128067850254,"score_spread":0.2136684759643144,"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."}}