{"id":"W3016654077","doi":"10.1175/jtech-d-19-0145.1","title":"EcoCTD for Profiling Oceanic Physical–Biological Properties from an Underway Ship","year":2020,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dynamic Systems Analysis (Canada)","funders":"Office of Naval Research Global; Woods Hole Oceanographic Institution","keywords":"Hydrography; Environmental science; Remote sensing; Profiling (computer programming); Oceanography; Software deployment; Sampling (signal processing); Computer science; Meteorology; Geology; Telecommunications; Geography","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":[0.0003155695,0.0005344808,0.0003332041,0.001066749,0.0002532679,0.0004489821,0.0005345835,0.0003799159,0.002345723],"category_scores_gemma":[0.0006380246,0.0001935255,0.0003410456,0.001074847,0.0001591847,0.0004885319,0.0009272291,0.0005138808,0.00102617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002798967,"about_ca_system_score_gemma":0.0006044841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008909224,"about_ca_topic_score_gemma":0.02379182,"domain_scores_codex":[0.9997775,0.00001586225,0.00001200316,0.0000744551,0.00009325475,0.00002692725],"domain_scores_gemma":[0.9995913,0.0000469697,0.00006181079,0.00009132925,0.0001443713,0.00006417199],"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":[0.001232577,0.0008734085,0.314189,0.000665849,0.000480096,0.001276402,0.0005679103,0.03637387,0.2979051,0.00175587,0.06946722,0.2752128],"study_design_scores_gemma":[0.00025069,0.0004852744,0.4516585,0.0000996762,0.0001473547,0.0005899774,0.00070906,0.4059972,0.07431797,0.001673605,0.06390059,0.0001701832],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7795031,0.0005234987,0.1057045,0.0004566542,0.0003752644,0.000440617,0.08310382,0.01605149,0.01384108],"genre_scores_gemma":[0.7847586,0.00022005,0.1458,0.0003440676,0.00007028689,0.0004415688,0.0635314,0.0005135132,0.004320635],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008909224,"threshold_uncertainty_score":0.01771474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02621751435041675,"score_gpt":0.2140128336138351,"score_spread":0.1877953192634183,"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."}}