{"id":"W2940427951","doi":"10.1080/14660466.2019.1592413","title":"Analyzing control, capacities, and benefits in Indigenous natural resource partnerships in Canada","year":2019,"lang":"en","type":"article","venue":"Environmental Practice","topic":"Mining and Resource Management","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Winnipeg","funders":"Social Sciences and Humanities Research Council of Canada; University of British Columbia; University of Northern British Columbia","keywords":"Indigenous; Natural resource; Resource (disambiguation); Environmental planning; Natural (archaeology); Environmental resource management; Control (management); Business; Natural resource economics; Geography; Political science; Environmental protection; Environmental science; Ecology; Computer science; Economics; Archaeology; Biology; Law; Management","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002400904,0.0001271186,0.0001474084,0.00007738745,0.00002893268,0.00001909625,0.00007740597,0.00003589147,0.00004004842],"category_scores_gemma":[0.00002160121,0.0001341827,0.00001160745,0.00006920464,0.00002221389,0.0001486688,0.00003466463,0.0003400008,0.00001809334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006367532,"about_ca_system_score_gemma":0.00001674397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09460583,"about_ca_topic_score_gemma":0.1422334,"domain_scores_codex":[0.9991356,0.00007161732,0.0001778193,0.0001736048,0.0001633212,0.0002779973],"domain_scores_gemma":[0.9995562,0.0002154666,0.00003796334,0.0001377098,6.616652e-7,0.00005198668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00015851,0.0000948231,0.4532027,0.0001431956,0.0001628095,0.0003584113,0.01029328,0.511604,0.000856253,0.0001056162,0.0007493733,0.02227105],"study_design_scores_gemma":[0.004655228,0.0001128168,0.5074936,0.0002048076,0.00008228284,0.0001068821,0.06777885,0.05384243,0.000374555,0.000006441373,0.3641585,0.001183713],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904512,0.002986192,0.000003364661,0.0001655314,0.00007095915,0.0001839019,0.000005653838,0.00001668499,0.006116549],"genre_scores_gemma":[0.99924,0.0001508631,0.00004987289,0.0002416004,0.00001878789,0.000008052558,0.000009101835,0.00001987814,0.0002618788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4577616,"threshold_uncertainty_score":0.9114233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006753344352924965,"score_gpt":0.1668189214194639,"score_spread":0.160065577066539,"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."}}