{"id":"W3124427048","doi":"","title":"Federal Court Interprets Canada's Technological Protection Measures for the First Time","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Education, Law, and Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Respondent; Federal court; Law; Political science; Business; Public administration; Supreme court","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":[0.005103192,0.0007911745,0.0008323062,0.002686848,0.02464835,0.007839927,0.003890949,0.01699014,0.008688105],"category_scores_gemma":[0.01949593,0.001057512,0.001707406,0.002759859,0.004344912,0.001557485,0.002337986,0.01314434,0.00169845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0544572,"about_ca_system_score_gemma":0.1536086,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9840937,"about_ca_topic_score_gemma":0.9925209,"domain_scores_codex":[0.9841462,0.0006727585,0.0004332221,0.001097011,0.008529607,0.005121214],"domain_scores_gemma":[0.9855527,0.003192927,0.00032191,0.0005661552,0.009362842,0.001003416],"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":[0.00007803832,0.00007380427,0.005566095,0.00008742228,0.00004791492,0.0005526017,0.004037033,0.0004237397,0.00135188,0.4527967,0.5183395,0.01664529],"study_design_scores_gemma":[0.00008340686,0.00008142161,0.01799901,0.0003469026,0.0002052142,0.0002017997,0.002906855,0.001062134,0.002175642,0.01780783,0.9568885,0.0002413237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05400659,0.002300166,0.007315404,0.1894857,0.004069168,0.0004179177,0.006232621,0.0007844705,0.735388],"genre_scores_gemma":[0.3923464,0.001572738,0.006055859,0.2647053,0.000866604,0.0003578521,0.001583937,0.0001737416,0.3323374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0544572,"threshold_uncertainty_score":0.3951165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692609993478269,"score_gpt":0.2873017900328535,"score_spread":0.2703756900980708,"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."}}