{"id":"W4394474326","doi":"10.6084/m9.figshare.1243183","title":"GIS Layer of Standardized Fish Mercury Concentrations Across Canada Now Available","year":2014,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Fish <Actinopterygii>; Environmental science; Fishery; Environmental chemistry; Geography; Biology; Chemistry; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0005107983,0.001049533,0.0006890909,0.004083124,0.00163883,0.002299261,0.001363488,0.0004559822,0.0520715],"category_scores_gemma":[0.001935432,0.0005413123,0.0008704636,0.01121903,0.0003459944,0.0006993625,0.001241095,0.0007912442,0.01345587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01614677,"about_ca_system_score_gemma":0.04110501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839042,"about_ca_topic_score_gemma":0.9882438,"domain_scores_codex":[0.999081,0.00003558573,0.0000511764,0.00013508,0.0005253701,0.000171749],"domain_scores_gemma":[0.9968231,0.00008400897,0.00008146732,0.0001370549,0.002693985,0.0001803736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000187588,0.00003672996,0.02117189,0.0005071798,0.0001071526,0.0001332778,0.0004433797,0.004178501,0.001681008,0.002778288,0.9127675,0.05600744],"study_design_scores_gemma":[0.0000731299,0.00001252789,0.07391142,0.000269354,0.00007480375,0.0000761833,0.001377162,0.006483382,0.002419984,0.001179754,0.9139784,0.0001438954],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006780004,0.0002101221,0.004879318,0.0004275506,0.00006652587,0.0002363261,0.9503237,0.002567301,0.03450914],"genre_scores_gemma":[0.03769729,0.0006911641,0.03225186,0.0002516849,0.00002003355,0.0004596165,0.8874983,0.0007973639,0.04033259],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0520715,"threshold_uncertainty_score":0.1741965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334050955471601,"score_gpt":0.2804100540166754,"score_spread":0.2470049584695153,"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."}}