{"id":"W2893690413","doi":"10.3390/w10101325","title":"What Participation? Distinguishing Water Monitoring Programs in Mining Regions Based on Community Participation","year":2018,"lang":"en","type":"article","venue":"Water","topic":"Mining and Resource Management","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of British Columbia","funders":"","keywords":"Stakeholder; Business; Citizen journalism; Resource (disambiguation); License; Quality (philosophy); Public relations; Conflict resolution; Environmental planning; Environmental resource management; Political science; Computer science; Geography; Environmental science","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":[0.006141118,0.0001806221,0.0002540248,0.001853908,0.002252459,0.001995257,0.001124049,0.001057049,0.00216179],"category_scores_gemma":[0.0189214,0.0001854924,0.0003023939,0.001475714,0.002397644,0.002903253,0.003984449,0.0007180807,0.000266276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002016355,"about_ca_system_score_gemma":0.003165156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0137251,"about_ca_topic_score_gemma":0.02678395,"domain_scores_codex":[0.9917535,0.004361221,0.0002824789,0.0007017201,0.0008133908,0.002087762],"domain_scores_gemma":[0.9850492,0.006195743,0.004554536,0.0008812117,0.001285972,0.002033436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002978283,0.00056078,0.7659804,0.0002271787,0.00005767196,0.001191893,0.1367445,0.0007766763,0.003618823,0.01021036,0.001139129,0.07919472],"study_design_scores_gemma":[0.00002692506,0.0003106617,0.7078078,0.0002786627,0.00005089092,0.0007566779,0.2674478,0.002809928,0.001641069,0.004525568,0.01429759,0.00004648286],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866624,0.0001003243,0.001780137,0.001033611,0.000009579703,0.0001076027,0.00004898728,0.00001272006,0.01024469],"genre_scores_gemma":[0.999157,0.00003523039,0.0003439633,0.00006708097,0.000003510233,0.00004549739,0.00002066286,0.000003707958,0.000323525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0137251,"threshold_uncertainty_score":0.03247768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07612238639522223,"score_gpt":0.2875702675005562,"score_spread":0.211447881105334,"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."}}