{"id":"W2511155652","doi":"10.3934/microbiol.2016.3.332","title":"Development of bioleaching: proteomics and genomics approach in metals extraction process","year":2016,"lang":"en","type":"article","venue":"AIMS Microbiology","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Custom Security Industries (Canada); University of Toronto","funders":"","keywords":"Bioleaching; Metaproteomics; Process (computing); Biochemical engineering; Proteomics; Genomics; Biotechnology; Chemistry; Biology; Computer science; Engineering; Biochemistry; Gene","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":[0.0007594755,0.0006713188,0.0007692427,0.0007366844,0.0003313778,0.001176607,0.0006441158,0.0008971752,0.0007888096],"category_scores_gemma":[0.0002809546,0.0002969424,0.0004991928,0.0007973676,0.0004188186,0.001446401,0.0008207592,0.001217292,0.0007750065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006500162,"about_ca_system_score_gemma":0.0008965378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004820105,"about_ca_topic_score_gemma":0.0005500684,"domain_scores_codex":[0.9995586,0.00008527511,0.00002442099,0.0001461006,0.000144355,0.00004121799],"domain_scores_gemma":[0.9998829,0.00002516021,0.000018153,0.000007886836,0.00004833623,0.0000175256],"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":[0.0001164181,0.00007634813,0.001110628,0.002092363,0.00005954408,0.0002570837,0.0001977534,0.0008540362,0.8541703,0.00793184,0.001113654,0.13202],"study_design_scores_gemma":[0.00003321393,0.0006443274,0.009010836,0.0003574671,0.0001854865,0.002333764,0.0004857641,0.01006991,0.7803859,0.01202167,0.1843569,0.0001147711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1556279,0.3302293,0.4803479,0.007630066,0.001184625,0.0003984668,0.0009493774,0.0009357057,0.02269668],"genre_scores_gemma":[0.3133367,0.2422799,0.4273967,0.002326332,0.000601069,0.0003833756,0.001228013,0.0001365084,0.01231131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001176607,"threshold_uncertainty_score":0.004716218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699780641991571,"score_gpt":0.2394966748936048,"score_spread":0.2224988684736891,"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."}}