{"id":"W1994532809","doi":"10.1504/ijep.2010.033234","title":"Appraising the Global Mercury Project: an adaptive management approach to combating mercury pollution in small-scale gold mining","year":2010,"lang":"en","type":"article","venue":"International Journal of Environment and Pollution","topic":"Mining and Resource Management","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mercury (programming language); Gold mining; Mercury pollution; Poverty; Business; Environmental planning; Pollution; Pollution prevention; Environmental science; Environmental protection; Environmental resource management; Engineering; Waste management; Economic growth; Computer science; Economics; Chemistry","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":[0.003535337,0.0004779404,0.0001811129,0.001219393,0.0009986627,0.002074199,0.000903242,0.001624531,0.001026174],"category_scores_gemma":[0.002982017,0.00007513742,0.0001690225,0.001134616,0.002223293,0.001318264,0.001950348,0.0006929451,0.0001371246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001477137,"about_ca_system_score_gemma":0.004024962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004398177,"about_ca_topic_score_gemma":0.01024886,"domain_scores_codex":[0.9975618,0.001379471,0.00005033176,0.0000890554,0.0007831642,0.0001361246],"domain_scores_gemma":[0.9986234,0.0005736155,0.0001308795,0.000061388,0.0004599913,0.0001508499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005245259,0.0008775553,0.04145808,0.002882315,0.00009637181,0.002273114,0.009112965,0.03635195,0.01159922,0.04840521,0.03891015,0.8075085],"study_design_scores_gemma":[0.0002284683,0.008358418,0.1038511,0.002418097,0.000217614,0.002062188,0.07170168,0.02095571,0.01524354,0.06795174,0.7067966,0.0002148635],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7042036,0.02082686,0.03036711,0.03739082,0.001181711,0.001533496,0.0002785569,0.0004212858,0.2037965],"genre_scores_gemma":[0.9332998,0.0171031,0.02958319,0.002638954,0.0002839355,0.0003037585,0.00018651,0.00007528976,0.01652534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004398177,"threshold_uncertainty_score":0.01869684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416677574490911,"score_gpt":0.229104385061948,"score_spread":0.2149376093170389,"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."}}