{"id":"W4399871618","doi":"10.3390/w16121745","title":"The Water Management Impacts of Large-Scale Mining Operations: A Social and Environmental Perspective","year":2024,"lang":"en","type":"article","venue":"Water","topic":"Mining and Resource Management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Business; Environmental resource management; Transparency (behavior); Water resources; Population; Government (linguistics); Resource management (computing); Focus group; Stewardship (theology); Environmental planning; Environmental economics; Resource (disambiguation); Geography; Environmental science; Political science; Economics; Marketing; Computer science; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008656015,0.0002262084,0.0001668757,0.0012007,0.002239541,0.002619269,0.0004091926,0.0005853999,0.003129195],"category_scores_gemma":[0.001334676,0.000114696,0.0001703207,0.001059404,0.004053404,0.001886243,0.002944579,0.0005041521,0.00009433659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003193583,"about_ca_system_score_gemma":0.002295224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01613323,"about_ca_topic_score_gemma":0.04795284,"domain_scores_codex":[0.9989116,0.0005618853,0.00001841799,0.00005536868,0.0001772606,0.000275376],"domain_scores_gemma":[0.9985974,0.0006770719,0.0003379864,0.00003308127,0.0001618779,0.0001925361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002028316,0.001191952,0.5246167,0.001121946,0.0002073631,0.007901216,0.2776946,0.00374968,0.009008588,0.05237261,0.005456136,0.1164764],"study_design_scores_gemma":[0.000007175864,0.0001920173,0.2921865,0.0002771596,0.00002674071,0.0003664063,0.6659824,0.001156097,0.0008875725,0.006731811,0.03215551,0.00003056367],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653292,0.0005765873,0.0003866467,0.004127084,0.00001403832,0.0000231305,0.00005260509,0.000002958222,0.02948778],"genre_scores_gemma":[0.9986752,0.0003731592,0.00006382407,0.00009511491,0.000008557207,0.000006163954,0.000009064895,0.000001045717,0.0007678932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01613323,"threshold_uncertainty_score":0.03207862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00505061631285455,"score_gpt":0.2058602527987286,"score_spread":0.2008096364858741,"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."}}