{"id":"W4408037702","doi":"10.1017/s1472669624000550","title":"Indigenous Legal Materials and Libraries: One Canadian Law Library's Experience","year":2024,"lang":"en","type":"article","venue":"Legal Information Management","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Law library; Political science; Library science; Law; Computer science","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01059138,0.0005689134,0.0008193318,0.004084104,0.1244375,0.02424169,0.005206115,0.006770591,0.01661308],"category_scores_gemma":[0.0221795,0.0009215202,0.0006113141,0.01168736,0.02867205,0.009502915,0.01845579,0.009076391,0.001265303],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1331492,"about_ca_system_score_gemma":0.2611895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9712385,"about_ca_topic_score_gemma":0.9914559,"domain_scores_codex":[0.9829061,0.004613402,0.0003370059,0.0006602849,0.005755182,0.00572796],"domain_scores_gemma":[0.9749179,0.007522075,0.0007216022,0.0007073588,0.005989435,0.01014161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006308551,0.0001860847,0.003862015,0.0002082169,0.00001591484,0.003042929,0.890083,0.0001145475,0.0002485471,0.0193349,0.04925669,0.0335841],"study_design_scores_gemma":[0.00001047979,0.00003546323,0.002714692,0.0001626116,0.00001423277,0.000513918,0.7052882,0.00005263295,0.0001353742,0.001018686,0.2899963,0.00005734143],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4164208,0.01191213,0.001240108,0.2111083,0.001648235,0.00031962,0.0003829769,0.0003507185,0.3566171],"genre_scores_gemma":[0.8400798,0.01067593,0.00162714,0.03621854,0.0003308878,0.0001074476,0.0001844222,0.0003232955,0.1104527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9757583,"threshold_uncertainty_score":0.9660694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02032287219458814,"score_gpt":0.2948630255496797,"score_spread":0.2745401533550916,"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."}}