{"id":"W6910964859","doi":"10.5065/d6tt4p1w","title":"SBI: 2003 Helo Survey ISUS Nitrate Concentrations, Temperature, Salinity, and Density. Version 1.0","year":2009,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"CTD; Sampling (signal processing); Transect; Nitrate; Current meter; Hydrology (agriculture)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007290026,0.0009873535,0.000768802,0.002694342,0.000320797,0.0008026215,0.001335543,0.000377599,0.033152],"category_scores_gemma":[0.001520706,0.0006269762,0.0004284212,0.00530058,0.0001155062,0.0006844664,0.0008089187,0.0005503466,0.02723032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125199,"about_ca_system_score_gemma":0.001222691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0699801,"about_ca_topic_score_gemma":0.09006391,"domain_scores_codex":[0.9996283,0.00003563006,0.00005739593,0.00008460206,0.0001342618,0.00005970418],"domain_scores_gemma":[0.9986081,0.0001069657,0.0002470247,0.0002483572,0.0006623647,0.0001273012],"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":[0.0001668414,0.00007220462,0.02759915,0.0003698405,0.00005255718,0.00004923307,0.0001635381,0.0009940589,0.001319554,0.0003216863,0.9516153,0.01727597],"study_design_scores_gemma":[0.0002223678,0.00004743143,0.3079913,0.0001430619,0.00004834461,0.0001351469,0.0004226592,0.003394889,0.003098072,0.0006350232,0.6837804,0.00008125561],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002856565,0.00001060636,0.0003523058,0.0000273426,0.00001299944,0.00003917098,0.9940499,0.000676471,0.001974709],"genre_scores_gemma":[0.00534813,0.00002355659,0.001988068,0.00004091436,0.000006317062,0.0002587227,0.9897714,0.0003213935,0.002241453],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0699801,"threshold_uncertainty_score":0.1391455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02062959826510544,"score_gpt":0.2570743608165365,"score_spread":0.2364447625514311,"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."}}