{"id":"W2167275501","doi":"10.1080/07055900.2014.986710","title":"Thermal Fronts Atlas of Canadian Coastal Waters","year":2014,"lang":"en","type":"article","venue":"ATMOSPHERE-OCEAN","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Université du Québec à Rimouski","funders":"Canadian Space Agency","keywords":"Oceanography; Phytoplankton; Environmental science; Front (military); Trophic level; Sea surface temperature; Satellite; Satellite imagery; High resolution; Atlas (anatomy); Biomass (ecology); Climatology; Remote sensing; Ecology; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.000194701,0.0004464113,0.0002300853,0.006022765,0.001538132,0.000863292,0.0004471064,0.0001519119,0.01002459],"category_scores_gemma":[0.0005046957,0.0001706063,0.0004203844,0.007902904,0.0002381887,0.0002395066,0.0004003337,0.000348028,0.001207508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01056812,"about_ca_system_score_gemma":0.01279601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928853,"about_ca_topic_score_gemma":0.9974279,"domain_scores_codex":[0.9997879,0.000009541919,0.000009973473,0.00003379135,0.00009987375,0.00005891905],"domain_scores_gemma":[0.9991558,0.00001557851,0.000057486,0.00002994972,0.0006552907,0.00008583706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003417502,0.0000648267,0.4159186,0.001135295,0.0002366116,0.0003165655,0.002236029,0.008193557,0.0120267,0.004205861,0.3303526,0.2249717],"study_design_scores_gemma":[0.00001474209,0.00001137961,0.8689617,0.00009211621,0.00003083321,0.00007405727,0.0006132726,0.001842816,0.0004366755,0.0001728741,0.1277233,0.00002636555],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2114515,0.003361535,0.00498238,0.0006990138,0.0002207574,0.0004100638,0.6785424,0.001262398,0.09906994],"genre_scores_gemma":[0.5792972,0.003994885,0.02751251,0.0002253977,0.00006999983,0.0003851419,0.3458935,0.0002928461,0.04232854],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01056812,"threshold_uncertainty_score":0.0766775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007925727168220022,"score_gpt":0.1963655540458229,"score_spread":0.1884398268776029,"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."}}