{"id":"W3215690133","doi":"","title":"New Data Analysis Capabilities in Ocean Networks Canada's Data Management Platform","year":2018,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Environmental Monitoring and Data Management","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Data management; Computer science; Data science; Business; Telecommunications; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009788293,0.0001974937,0.000218362,0.0001282782,0.0001659468,0.0001415137,0.001818344,0.00005000022,0.00007303939],"category_scores_gemma":[0.00006004712,0.0001848684,0.00002037028,0.00040053,0.00006455042,0.0005925323,0.0005186875,0.0001651534,0.00004473771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003526473,"about_ca_system_score_gemma":0.00005590513,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9799991,"about_ca_topic_score_gemma":0.9946268,"domain_scores_codex":[0.9977737,0.00003327855,0.0004216169,0.0007975146,0.0004588981,0.000514972],"domain_scores_gemma":[0.9974229,0.0001522117,0.000132777,0.002083626,0.000005805482,0.0002026347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001373927,0.00001258291,0.8964257,0.00001767424,0.0001637549,0.00006312463,0.00004398724,0.06515566,5.555516e-8,0.000004988228,0.01316734,0.02493137],"study_design_scores_gemma":[0.0001598409,0.00002412748,0.9428139,0.00004247546,0.0001655438,0.000001206306,0.0004919741,0.03773706,0.00000194738,0.00003455569,0.0183089,0.0002184669],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627467,0.0004386065,0.0001830598,0.0002869137,0.000830684,0.0002260211,0.0005763574,0.00005881238,0.0346528],"genre_scores_gemma":[0.9886616,0.0001291644,0.004286936,0.0001620861,0.0004018747,2.627454e-7,0.005721703,0.00000609869,0.0006302412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04638819,"threshold_uncertainty_score":0.7538714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03107260153243248,"score_gpt":0.2303755243882848,"score_spread":0.1993029228558523,"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."}}