{"id":"W3112156306","doi":"10.3390/foods9121824","title":"Identification of Arctic Food Fish Species for Anthropogenic Contaminant Testing Using Geography and Genetics","year":2020,"lang":"en","type":"article","venue":"Foods","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Carleton University; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Northern Contaminants Program; Ontario Genomics; Genome Canada","keywords":"Fish migration; Arctic char; Salvelinus; Arctic; Trout; Fishery; Fishing; Congener; Pollutant; Brown trout; Population; Ecology; Marine Strategy Framework Directive; Environmental science; Grayling; Geography; Biology; Fish <Actinopterygii>; Environmental chemistry; Ecosystem; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008055533,0.00006222875,0.0001000156,0.00001421233,0.0001111274,0.00001461795,0.00004925843,0.00001858837,0.00003340204],"category_scores_gemma":[0.0001347497,0.00005874651,0.00003086709,0.0001483043,0.0001905706,0.00006187247,0.00005620398,0.00002230564,0.000001283373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001161699,"about_ca_system_score_gemma":0.000003919208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001652007,"about_ca_topic_score_gemma":0.00001155302,"domain_scores_codex":[0.9994786,0.00001248129,0.0001788358,0.000128628,0.00009600211,0.000105482],"domain_scores_gemma":[0.9997039,0.00006172876,0.0001062673,0.00006402981,0.00001751164,0.00004655431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009792427,0.00002077332,0.6194039,0.00008571937,0.00003490198,2.02559e-7,0.001197822,0.0001671039,0.3753056,0.0000363544,0.0001036078,0.003634232],"study_design_scores_gemma":[0.0003112712,0.0004595935,0.8969151,0.00001507954,0.00007003672,0.000002900346,0.0007334261,0.006225848,0.09397045,0.0002407163,0.0009277611,0.0001277649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939364,0.0001584153,0.005351882,0.000175985,0.00004747081,0.0001884701,0.00005352091,0.00001007161,0.00007774757],"genre_scores_gemma":[0.9970106,0.00003768427,0.002804117,0.00009457798,0.00003073229,0.000005126255,0.000003326184,0.000005918271,0.000007933531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2813351,"threshold_uncertainty_score":0.2395613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07560930976369078,"score_gpt":0.2864674762138211,"score_spread":0.2108581664501303,"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."}}