{"id":"W7096567509","doi":"","title":"1 BASELINE SELENIUM IN SCULPINS RELATED TO THE NORTHEAST BRITISH COLUMBIA COAL ZONE","year":2015,"lang":"en","type":"article","venue":"","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sculpin; Coal; Selenium; Coal mining; Fish <Actinopterygii>; Baseline (sea)","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":[0.0001061937,0.0004139277,0.0003391364,0.001289005,0.001836104,0.0006556901,0.0003199009,0.000417659,0.001248901],"category_scores_gemma":[0.0003830248,0.0002270927,0.0001271237,0.0009384383,0.0005076119,0.0001486915,0.0004313752,0.0002605558,0.0003165633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002459972,"about_ca_system_score_gemma":0.001453805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6307202,"about_ca_topic_score_gemma":0.8407409,"domain_scores_codex":[0.99977,0.00001176129,0.00001372837,0.00007031764,0.000079322,0.00005488682],"domain_scores_gemma":[0.9995784,0.00001492261,0.00006577123,0.00001658336,0.0002438939,0.00008041309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000282899,0.00009479462,0.9708651,0.00002783923,0.00002473214,0.0005662022,0.0009472273,0.00008418,0.02306967,0.00001893904,0.0002440526,0.003774404],"study_design_scores_gemma":[0.000001054679,0.00008596326,0.9986657,0.000003853304,0.000004749355,0.00009447153,0.0004326346,0.00002828656,0.0004654714,0.000003590239,0.0002124428,0.000001856666],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982492,0.00006936689,0.00004886998,0.000008188986,0.000001713554,0.00001873532,0.0005484134,0.000006093912,0.001049577],"genre_scores_gemma":[0.9966046,0.0001024314,0.0001410015,0.00004007441,0.000001477317,0.00002293758,0.001271286,0.000004662265,0.001811605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3692798,"threshold_uncertainty_score":0.7429091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01709227087358367,"score_gpt":0.2416789705258953,"score_spread":0.2245866996523116,"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."}}