{"id":"W2962569369","doi":"10.3389/fmars.2019.00410","title":"The Joint IOC (of UNESCO) and WMO Collaborative Effort for Met-Ocean Services","year":2019,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Fisheries and Oceans Canada","funders":"National Oceanic and Atmospheric Administration; Natural Environment Research Council; European Commission; Sight Research UK; Joint Institute for the Study of the Atmosphere and Ocean","keywords":"Interoperability; Commission; Joint (building); Business; Engineering management; Environmental resource management; Process management; Computer science; Operations research; Engineering; Environmental science; World Wide Web; Finance; Civil engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006530685,0.0001149741,0.0001615811,0.00001304999,0.0001852881,0.0000363618,0.0004197205,0.0000304713,0.00003748283],"category_scores_gemma":[0.00001601433,0.00008130116,0.00002457829,0.0005273949,0.001277367,0.00029386,0.0006749326,0.00006718374,0.000005777429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001610529,"about_ca_system_score_gemma":0.00002040012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001143952,"about_ca_topic_score_gemma":0.00002911922,"domain_scores_codex":[0.9988365,0.00001389973,0.0001965791,0.0003388078,0.0003137062,0.0003005207],"domain_scores_gemma":[0.9995418,0.00002754886,0.0001081072,0.0002462935,0.000007825238,0.00006848864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003152441,0.00002070843,0.9703557,0.00001473587,0.00000412495,3.865672e-7,0.0003683673,0.00635849,0.0008971617,0.0002457982,0.0001454499,0.0215575],"study_design_scores_gemma":[0.0006628477,0.0002857734,0.9144466,0.00002188215,0.00001217579,0.000002301735,0.005272218,0.0647928,0.001181592,0.00599865,0.007063735,0.000259456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942139,0.0000639804,0.001760357,0.00009156398,0.0003792321,0.0004838161,0.000002327521,0.000007559827,0.002997278],"genre_scores_gemma":[0.8331569,0.0002055706,0.1651201,0.00008564201,0.000007315787,0.00001187876,0.000001377908,0.000008848054,0.001402324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1633598,"threshold_uncertainty_score":0.470651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002237340265827418,"score_gpt":0.1845288433347326,"score_spread":0.1822915030689052,"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."}}