{"id":"W4256302781","doi":"10.1201/b12350-7","title":"Giant Mine,Yellowknife, Canada: Arsenite waste as the legacy of gold mining and processing","year":2016,"lang":"en","type":"book-chapter","venue":"","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Arsenite; Mining engineering; Geology; Geochemistry; Metallurgy; Arsenic; Materials science","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":[0.0002865567,0.001068975,0.0004181327,0.001860971,0.005474838,0.004245931,0.0008832958,0.00146242,0.01182134],"category_scores_gemma":[0.0003678998,0.0003024458,0.0002687084,0.004178483,0.002654111,0.00154691,0.001255428,0.00179942,0.002249321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0252296,"about_ca_system_score_gemma":0.04954692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8957127,"about_ca_topic_score_gemma":0.9831065,"domain_scores_codex":[0.9996899,0.00001160444,0.000006671355,0.00003018063,0.0002049078,0.00005678498],"domain_scores_gemma":[0.9998492,0.00001735616,0.000006329946,0.000006332035,0.00009343957,0.00002735276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000585609,0.00003287385,0.000877662,0.000601567,0.00001062447,0.0005667107,0.006256362,0.0006298616,0.00229477,0.1395926,0.5984865,0.2505919],"study_design_scores_gemma":[0.000001088651,0.000004286768,0.0006202487,0.0002004953,0.000002998117,0.0001436561,0.001164461,0.00004424644,0.0002743105,0.00395434,0.9935828,0.000007077871],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007558355,0.2383875,0.002278162,0.01347642,0.003616964,0.00007336176,0.0009520369,0.0001779188,0.7334793],"genre_scores_gemma":[0.016213,0.0828835,0.001492958,0.00129801,0.000211844,0.00001473764,0.0002601306,0.0001099875,0.8975159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1042873,"threshold_uncertainty_score":0.2098029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235766948347563,"score_gpt":0.1941880289583654,"score_spread":0.1818303594748897,"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."}}