{"id":"W2171545414","doi":"10.46989/001c.20614","title":"Low Mercury Levels in Lake Kinneret Fish","year":2012,"lang":"en","type":"article","venue":"Israeli Journal of Aquaculture - Bamidgeh","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Fisheries and Oceans Canada","funders":"","keywords":"Biomagnification; Methylmercury; Trophic level; Mercury (programming language); Freshwater fish; Bioaccumulation; Fishery; Predatory fish; Fish <Actinopterygii>; Food web; Lake ecosystem; Ecology; Environmental chemistry; Biology; Ecosystem; Zoology; 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":[0.0001219552,0.0002392348,0.000224488,0.0007125037,0.0006009638,0.0004408953,0.0002044859,0.0003584481,0.00126794],"category_scores_gemma":[0.000243708,0.0002001522,0.0001511258,0.0003787518,0.0004538675,0.0003469961,0.000528283,0.0001875412,0.000280281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007505306,"about_ca_system_score_gemma":0.0003465115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01798002,"about_ca_topic_score_gemma":0.04901204,"domain_scores_codex":[0.9998904,0.000007370489,0.00001015262,0.00003712859,0.000034436,0.00002050846],"domain_scores_gemma":[0.999881,0.00001015938,0.00004020605,0.000007301842,0.00004137774,0.0000199696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008067655,0.0000952094,0.5155779,0.0001052644,0.00006372738,0.0007708554,0.003833717,0.0002694786,0.4702235,0.0001174719,0.0001040876,0.008031991],"study_design_scores_gemma":[0.00001428898,0.0002961648,0.9813781,0.000008592662,0.00003252038,0.0003298948,0.001706845,0.0002079607,0.01527018,0.00005753855,0.0006788694,0.00001897659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995376,0.00001596597,0.00002033138,0.000004424805,5.25741e-7,0.000001255327,0.00003217891,0.000001734591,0.0003861059],"genre_scores_gemma":[0.9985608,0.00002907729,0.0001270109,0.00001889499,9.63664e-7,0.000007006825,0.0001165505,0.000002583504,0.001137062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01798002,"threshold_uncertainty_score":0.03575069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380637451707031,"score_gpt":0.2753060435359909,"score_spread":0.2514996690189206,"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."}}