{"id":"W7002017242","doi":"","title":"Making Canadian Indian Policy: The Hidden Agenda 1968–1970","year":2023,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Metallurgy and Cultural Artifacts","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); White paper; Public policy; White (mutation); 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":[0.005409909,0.0007564652,0.0003850475,0.003855594,0.03385228,0.01179459,0.001848342,0.003733203,0.01261417],"category_scores_gemma":[0.01561687,0.0006930042,0.0005044622,0.008029726,0.01766937,0.003402583,0.003602648,0.006767382,0.0008821452],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.3557958,"about_ca_system_score_gemma":0.3346014,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962573,"about_ca_topic_score_gemma":0.9980192,"domain_scores_codex":[0.993109,0.0009724664,0.0001683526,0.0004618874,0.00254488,0.002743473],"domain_scores_gemma":[0.9954411,0.001188898,0.0001584273,0.0002021194,0.002337753,0.000671725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008128493,0.00003806229,0.001957468,0.0001738025,0.00001969774,0.0004753664,0.06963768,0.0007546065,0.0004559743,0.7625637,0.1231886,0.04065378],"study_design_scores_gemma":[0.00001273988,0.000007375609,0.005269113,0.0002095224,0.00002088944,0.00004914445,0.02255286,0.0001818162,0.0004265745,0.01002857,0.9611875,0.00005407932],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07085701,0.01100426,0.001839085,0.1231517,0.001625144,0.0001913122,0.001293447,0.00009801125,0.78994],"genre_scores_gemma":[0.7228233,0.008452581,0.002538272,0.01426207,0.0003398507,0.0001496795,0.000431527,0.0002092981,0.2507935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3557958,"threshold_uncertainty_score":0.7471855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06815723473460661,"score_gpt":0.2923897015483271,"score_spread":0.2242324668137204,"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."}}