{"id":"W4244852844","doi":"10.1139/f99-262","title":"Estimating food consumption rates of fish using a mercury mass balance model","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy balance; Food consumption; Mercury (programming language); Environmental science; Fish <Actinopterygii>; Food intake; Animal science; Fishery; Biology; Ecology; Toxicology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0007187061,0.0007667942,0.0004932631,0.0007244259,0.0003093058,0.0003625228,0.0008780404,0.0004878313,0.001246885],"category_scores_gemma":[0.001682977,0.0003724668,0.000541173,0.0004683638,0.0002594341,0.0004366777,0.0003023277,0.0002868415,0.0003426523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002081885,"about_ca_system_score_gemma":0.001099107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.167177,"about_ca_topic_score_gemma":0.147296,"domain_scores_codex":[0.9997706,0.00003481987,0.00001254904,0.00007539678,0.00008474363,0.00002195354],"domain_scores_gemma":[0.999546,0.0001967099,0.0001116689,0.00004213853,0.00008980401,0.00001367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005168729,0.0001736356,0.169921,0.0002205456,0.0005809788,0.0001911603,0.0003011475,0.6915991,0.0463902,0.002000405,0.00139637,0.08670858],"study_design_scores_gemma":[0.00004682537,0.0001934918,0.06315771,0.00001176383,0.00009268391,0.00006360699,0.0000335412,0.927598,0.006470318,0.0009776016,0.001306261,0.00004813976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6118701,0.0001594345,0.3809302,0.0001096078,0.00001495051,0.0002642816,0.00177098,0.001170326,0.003710225],"genre_scores_gemma":[0.9130343,0.0001370038,0.08185065,0.00004010331,0.000006197361,0.0003565436,0.001072968,0.00006826372,0.003434133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.167177,"threshold_uncertainty_score":0.3324078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05311219152108021,"score_gpt":0.2724478887168425,"score_spread":0.2193356971957623,"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."}}