{"id":"W4385726829","doi":"10.1126/science.adi0658","title":"Cultural water and Indigenous water science","year":2023,"lang":"en","type":"article","venue":"Science","topic":"Water resources management and optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Indigenous; Environmental science; Environmental resource management; Environmental planning; Environmental ethics; Natural resource economics; Geography; Ecology; Biology; Economics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003644447,0.00005307595,0.00003591722,0.0002162524,0.0003310298,0.0002689773,0.0002487364,0.000009385846,0.00001368453],"category_scores_gemma":[0.00000443924,0.0000290677,0.000006006211,0.0005411866,0.0004166292,0.0006211636,0.0001638758,0.0000306811,0.0002290606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000251083,"about_ca_system_score_gemma":0.000003964049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003296738,"about_ca_topic_score_gemma":9.445685e-7,"domain_scores_codex":[0.9991546,0.000001816772,0.00005470058,0.0001555701,0.0002388505,0.0003944536],"domain_scores_gemma":[0.9998199,0.000001358722,0.000002575438,0.00009555358,0.00002629437,0.00005426389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001613992,0.00000464413,0.002331024,0.00004241843,0.00000342098,0.00001105574,0.0500357,0.1108072,0.8305688,0.00007881918,0.0001676193,0.005947732],"study_design_scores_gemma":[0.0001499589,0.00002449998,0.01141734,0.000009716278,0.000004622971,0.000005053704,0.0007724615,0.175918,0.80103,0.0002849895,0.0101168,0.0002665498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966299,0.00001035821,0.0001196676,0.00005644933,0.0002044531,0.00006873807,2.604111e-7,0.0002557161,0.002654459],"genre_scores_gemma":[0.9991532,0.00001618404,0.0001437466,0.00001834489,0.00002067171,0.000003436054,0.000003494701,0.000004568604,0.0006363434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06511083,"threshold_uncertainty_score":0.2944187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009036564299087254,"score_gpt":0.2060454347169136,"score_spread":0.1970088704178264,"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."}}