{"id":"W2975420940","doi":"10.1029/2019eo134291","title":"Indigenous Knowledge Puts Industrial Pollution in Perspective","year":2019,"lang":"en","type":"article","venue":"Eos","topic":"Mining and Resource Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Perspective (graphical); Pollution; Industrial pollution; Environmental planning; Environmental science; Business; Geography; Computer science; Ecology; Artificial intelligence","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":[0.002398659,0.0003361484,0.0004771338,0.00234528,0.00950489,0.007414638,0.001124422,0.002399803,0.007763739],"category_scores_gemma":[0.004200592,0.0001690598,0.0003491244,0.002652589,0.03075334,0.006689422,0.005249503,0.003543285,0.0004337952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01633623,"about_ca_system_score_gemma":0.02649928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5305904,"about_ca_topic_score_gemma":0.7408978,"domain_scores_codex":[0.9976011,0.0004751297,0.00005835409,0.0002352,0.0009863914,0.000643845],"domain_scores_gemma":[0.9959614,0.00152955,0.0003646156,0.0004632319,0.001345651,0.0003355905],"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":[0.00008017355,0.0001378309,0.01999903,0.0008877903,0.0001179832,0.001879674,0.2172872,0.001437185,0.002820192,0.5573282,0.0322234,0.1658013],"study_design_scores_gemma":[0.000009905702,0.0000553351,0.01985995,0.00120429,0.00007935418,0.0003756853,0.1768834,0.0003577688,0.001246368,0.1966117,0.6032564,0.00005985908],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1443736,0.01297261,0.007355146,0.181037,0.001052095,0.00003371025,0.000296098,0.00008083144,0.652799],"genre_scores_gemma":[0.9477755,0.01068177,0.002371824,0.008414163,0.0003360784,0.00001749405,0.00009110373,0.00004214585,0.03026975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5305904,"threshold_uncertainty_score":0.9443481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131600809765244,"score_gpt":0.2161291286722385,"score_spread":0.2029690476957141,"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."}}