{"id":"W3018853292","doi":"10.1002/eap.2146","title":"Using Indigenous and Western knowledge systems for environmental risk assessment","year":2020,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Indigenous; Ecology; Traditional knowledge; Geography; Risk assessment; Environmental resource management; Environmental protection; Environmental science; Biology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001315157,0.000147174,0.000179438,0.000008450529,0.0005056128,0.00005193925,0.0001648819,0.00009698272,0.0002860239],"category_scores_gemma":[0.000007948582,0.0001286148,0.00005168419,0.00007822405,0.0001980056,0.0001240871,0.0002575668,0.0001312174,0.0002110445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002982249,"about_ca_system_score_gemma":0.000008418204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002852124,"about_ca_topic_score_gemma":0.000007559637,"domain_scores_codex":[0.9989618,0.00006371296,0.0002190787,0.0003662829,0.0001276479,0.0002614956],"domain_scores_gemma":[0.9994171,0.0001024502,0.0001155322,0.0001134007,0.000001474438,0.000250019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008385749,0.00073316,0.9816788,0.0000161233,0.00003284813,0.000001095052,0.0009165675,0.0013352,0.007231455,0.000103834,0.0001700697,0.00777245],"study_design_scores_gemma":[0.0004996338,0.0003134946,0.9442759,0.000001977479,0.00006832654,0.000004141893,0.0005214354,0.009084226,0.00005003937,0.0004114403,0.04449395,0.0002755042],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551929,0.0001315594,0.04020792,0.0001672791,0.00003511569,0.001729269,0.0001648102,0.00005209849,0.002319096],"genre_scores_gemma":[0.9947682,0.000141545,0.003836149,0.0002744259,0.0001019547,0.0006307538,0.00003322641,0.0000149128,0.000198804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04432388,"threshold_uncertainty_score":0.5244758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04374448591244377,"score_gpt":0.3259746543695334,"score_spread":0.2822301684570896,"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."}}