{"id":"W2954081892","doi":"10.3389/fmars.2019.00440","title":"Ocean FAIR Data Services","year":2019,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Research Data Management Practices","field":"Computer Science","cited_by":244,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Natural Environment Research Council; Instituto Nacional de Ciência e Tecnologia - Oceanografia Integrada e Usos Múltiplos da Plataforma Continental e Oceano Adjacente - Centro de Oceanografia Integrada; LifeWatch – Niclas Öberg Foundation; Executive Agency for Small and Medium-sized Enterprises; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Oceanic and Atmospheric Administration; Sight Research UK; Horizon 2020 Framework Programme; Joint Institute for the Study of the Atmosphere and Ocean; California Institute of Technology","keywords":"Interoperability; Metadata; Computer science; Workflow; Data quality; Data management; Standardization; Data discovery; Data access; Data science; Data curation; World Wide Web; Database; Service (business); Business","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":["metaresearch","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005825851,0.001445953,0.001244332,0.007218667,0.003145283,0.01162124,0.005730507,0.004602238,0.3305979],"category_scores_gemma":[0.02591965,0.0008895335,0.001181759,0.01101915,0.001545012,0.01107444,0.01435994,0.003014925,0.2746058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003452929,"about_ca_system_score_gemma":0.006037501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0161493,"about_ca_topic_score_gemma":0.01050263,"domain_scores_codex":[0.9948031,0.0007633193,0.0005080254,0.0005768802,0.002638676,0.00070996],"domain_scores_gemma":[0.9892969,0.001762045,0.0004993499,0.003781042,0.003262295,0.001398475],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001521568,0.00003399296,0.0007921983,0.0002611034,0.00001973838,0.0001811607,0.0002274849,0.000361252,0.0004790243,0.01974323,0.9142058,0.06354284],"study_design_scores_gemma":[0.00002567742,0.000004644672,0.0002356181,0.0000590148,0.000003033824,0.00005056292,0.00008595901,0.0005775095,0.0002324298,0.005626143,0.9930776,0.00002187437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.001996655,0.002039406,0.03830212,0.0118609,0.002799495,0.0007928741,0.1300232,0.1251823,0.6870031],"genre_scores_gemma":[0.03994336,0.004118985,0.06465896,0.01127101,0.002175204,0.001885909,0.3824826,0.0504981,0.4429659],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9942695,"threshold_uncertainty_score":0.9548209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03631867215974199,"score_gpt":0.3169767745783257,"score_spread":0.2806581024185837,"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."}}