{"id":"W3163541738","doi":"10.5751/es-12265-260222","title":"Fostering horizontal knowledge co-production with Indigenous people by leveraging researchers' transdisciplinary intentions","year":2021,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Knowledge production; Production (economics); Indigenous; Knowledge management; Traditional knowledge; Environmental resource management; Business; Geography; Computer science; Environmental science; Ecology; Economics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","sts"],"domain":"methods","study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.04561162,0.0005848082,0.0003525384,0.002550155,0.004675034,0.007693626,0.001466054,0.001732798,0.005400898],"category_scores_gemma":[0.08463395,0.0005485924,0.0005775547,0.001247611,0.004723697,0.00560575,0.02536511,0.002674382,0.001763023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002642789,"about_ca_system_score_gemma":0.01851043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002333248,"about_ca_topic_score_gemma":0.005430522,"domain_scores_codex":[0.9711328,0.01885763,0.000758139,0.00170064,0.004742427,0.002808357],"domain_scores_gemma":[0.8880148,0.06311259,0.01062363,0.009936452,0.01012925,0.01818321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002988594,0.00407039,0.150042,0.001392426,0.0002123173,0.00123085,0.2296266,0.0008596578,0.01923702,0.02113144,0.01073716,0.5611613],"study_design_scores_gemma":[0.0004872223,0.004255168,0.1882555,0.005455918,0.0007076233,0.001858904,0.405007,0.007400109,0.02308597,0.1095868,0.2535141,0.0003856773],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7754938,0.001923878,0.06025072,0.04613413,0.0005420382,0.001083201,0.000068732,0.0005715485,0.1139319],"genre_scores_gemma":[0.9655445,0.0005855722,0.02779379,0.001553119,0.00007756353,0.0004766388,0.00003600757,0.00005682663,0.003875909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.995325,"threshold_uncertainty_score":0.2412202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08021382987634944,"score_gpt":0.4018805022303963,"score_spread":0.3216666723540469,"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."}}