{"id":"W1997136554","doi":"10.1007/s00128-004-0420-2","title":"Mercury and Other Contaminants in Fish from Lake Chad, Africa","year":2004,"lang":"en","type":"article","venue":"Bulletin of Environmental Contamination and Toxicology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Mercury (programming language); Mercury contamination; Ecotoxicology; Contamination; Fish <Actinopterygii>; Environmental science; Water pollution; Environmental chemistry; Fishery; Water pollutants; Environmental protection; Ecology; Geography; Biology; 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":[0.0001469425,0.0003834005,0.0002570082,0.001541506,0.001766965,0.000600258,0.0002401267,0.0004354406,0.001071159],"category_scores_gemma":[0.0003517198,0.0003369517,0.0002217646,0.001156819,0.0005860084,0.000329554,0.0004786603,0.0002818986,0.000349986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001241757,"about_ca_system_score_gemma":0.0007075462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09109984,"about_ca_topic_score_gemma":0.1382001,"domain_scores_codex":[0.99989,0.000008436003,0.000009186006,0.00002455229,0.00003757956,0.00003030014],"domain_scores_gemma":[0.9998558,0.00001835806,0.00003993524,0.000003108053,0.00005775599,0.00002497975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002415374,0.0001804063,0.8448743,0.000329757,0.0001349038,0.00255051,0.007527466,0.0004722769,0.1296199,0.0001532761,0.0003177171,0.01142399],"study_design_scores_gemma":[0.00001886633,0.0004474435,0.9850041,0.00001444681,0.00005869735,0.0007553807,0.0035695,0.0001743531,0.008326691,0.00005597859,0.001561638,0.00001294703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993129,0.0000594,0.00001791488,0.00001376672,0.000001598855,0.000004219326,0.0001394611,0.000001103292,0.0004497182],"genre_scores_gemma":[0.9973903,0.0002000279,0.0001097378,0.00002524365,0.000002920754,0.000008765125,0.0001599904,0.000002173509,0.002100739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09109984,"threshold_uncertainty_score":0.1811392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210973876821671,"score_gpt":0.2217549021928514,"score_spread":0.2096451634246347,"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."}}