{"id":"W1990542943","doi":"10.1007/s10646-011-0715-0","title":"Spatiotemporal trends of mercury in walleye and largemouth bass from the Laurentian Great Lakes Region","year":2011,"lang":"en","type":"article","venue":"Ecotoxicology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Micropterus; Mercury (programming language); Wildlife; Fishery; Environmental science; Bass (fish); Habitat; Geography; Ecology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001393906,0.00008555663,0.0001533235,0.00003413051,0.00005538243,0.000003554109,0.0001082897,0.00006762351,0.004352857],"category_scores_gemma":[0.00002242843,0.00005973194,0.0000269439,0.0001220632,0.0003174914,0.00008946058,0.00009694081,0.00007663871,0.00003296954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002363628,"about_ca_system_score_gemma":0.000004429794,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750336,"about_ca_topic_score_gemma":0.02882841,"domain_scores_codex":[0.9993353,0.0001041219,0.0001719931,0.0001609877,0.00007492297,0.0001526197],"domain_scores_gemma":[0.9996637,0.00006469091,0.00008625477,0.0001426415,0.000003489479,0.00003928939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003095941,0.00005652159,0.9682249,0.000002050361,0.00001726105,0.000006957366,0.008071704,0.000001984029,0.001031773,0.0001449168,0.007808793,0.01460222],"study_design_scores_gemma":[0.0003437886,0.00007923383,0.9906994,0.000005404275,0.0000128798,0.000002688593,0.0006889703,0.00004093147,0.001710119,0.0007551657,0.005587248,0.00007421686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868497,0.0001315648,0.00004553152,0.0007600638,0.0001026681,0.00008054764,0.00001308882,0.000009816102,0.01200701],"genre_scores_gemma":[0.9989927,0.00006171355,0.0001268003,0.0002455085,0.00001651269,0.00001104133,0.00001079731,0.000005214099,0.0005296908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02707808,"threshold_uncertainty_score":0.9965573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03585691858398159,"score_gpt":0.2468760198275869,"score_spread":0.2110191012436053,"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."}}