{"id":"W4240893532","doi":"10.1139/f00-126","title":"Mercury concentrations in northern pike ( <i>Esox lucius</i>) from boreal lakes with logged, burned, or undisturbed catchments","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":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Esox; Pike; Mercury (programming language); Environmental science; Trophic level; Boreal; Zooplankton; Hydrology (agriculture); Environmental chemistry; Ecology; Fishery; Chemistry; Biology; Geology; Fish <Actinopterygii>","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002283888,0.0001154795,0.0001889874,0.00005024718,0.0003634519,0.0001475234,0.0001897151,0.00002791017,0.001974108],"category_scores_gemma":[0.00005331626,0.00007312585,0.00002249131,0.0003441478,0.001128802,0.0004823299,0.000007622004,0.00008984157,0.00001452908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008377753,"about_ca_system_score_gemma":0.0003444036,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05399477,"about_ca_topic_score_gemma":0.7306596,"domain_scores_codex":[0.9989794,0.00004485291,0.0002789954,0.0001516331,0.0002613034,0.0002838327],"domain_scores_gemma":[0.9993632,0.00008832471,0.0001183228,0.00007196042,0.000009593541,0.0003486161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002356467,0.00001132505,0.9822553,0.000001321408,0.00001297788,0.00005000699,0.004738956,0.00006482026,0.00003765575,0.000009423108,0.001462057,0.01133257],"study_design_scores_gemma":[0.001001412,0.0006322949,0.9553884,0.0001185348,0.00004524386,0.00009055928,0.01192828,0.0002160681,0.0001040024,0.001210222,0.02895891,0.0003060276],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897434,0.0003076324,0.00001940207,0.002189219,0.00007627458,0.00008531108,0.00001677382,0.000002510419,0.007559485],"genre_scores_gemma":[0.9984005,0.0001421872,0.0004368474,0.0005244637,0.00003411149,0.000002680333,0.000003050505,0.000004005347,0.0004521679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6766648,"threshold_uncertainty_score":0.9989382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597369257468221,"score_gpt":0.2263168178966845,"score_spread":0.2103431253220023,"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."}}