{"id":"W2781608527","doi":"","title":"Implementing controlled vocabularies and international standards in web services to promote data interoperability: A case study","year":2017,"lang":"en","type":"article","venue":"OCEANS 2017 – Anchorage","topic":"Environmental Monitoring and Data Management","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Networks Canada Society; University of Victoria","funders":"","keywords":"Interoperability; Computer science; World Wide Web; Metadata; Data exchange","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001751911,0.0001482529,0.0002240638,0.00007763715,0.0005177326,0.0008815631,0.0008675616,0.00002399512,0.000193738],"category_scores_gemma":[0.00007023294,0.0001212914,0.00001618627,0.00002822745,0.00005940237,0.0009924979,0.0007479272,0.0001096082,0.00001755315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001470883,"about_ca_system_score_gemma":0.00001629058,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.006646715,"about_ca_topic_score_gemma":0.07687928,"domain_scores_codex":[0.9985978,0.00006283974,0.0002551461,0.0005158686,0.0002833781,0.0002849501],"domain_scores_gemma":[0.9986869,0.00002639626,0.0001107189,0.001055451,0.00001780501,0.0001027943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001436969,0.00006741667,0.9437233,0.00001880549,0.00004473237,0.000895665,0.001184995,0.00001581681,0.00001000159,0.000001524498,0.0001212232,0.05377281],"study_design_scores_gemma":[0.006591226,0.0005528059,0.9047989,0.0001294173,0.0000835545,0.0001312697,0.01823612,0.02066504,0.000007749704,0.0000493818,0.0482999,0.0004545812],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953648,0.0001577342,0.0000285513,0.0003325452,0.0003705479,0.0006820919,0.00136491,0.00001825168,0.001680503],"genre_scores_gemma":[0.9990625,0.00005956718,0.0003426303,0.00004474832,0.0001135122,0.000004416154,0.0001639316,0.000004338741,0.0002043338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07023256,"threshold_uncertainty_score":0.9999681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03825123707917589,"score_gpt":0.3216570532518916,"score_spread":0.2834058161727158,"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."}}