{"id":"W2915363558","doi":"10.1016/j.chemgeo.2018.05.040","title":"The GEOTRACES Intermediate Data Product 2017","year":2018,"lang":"en","type":"article","venue":"Chemical Geology","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":406,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of British Columbia","funders":"Natural Environment Research Council; Universitat Autònoma de Barcelona; Exzellenzcluster Ozean der Zukunft; Université Toulouse III - Paul Sabatier; Ministry of Earth Sciences; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research; Centre National de la Recherche Scientifique; University of Tokyo; GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel; University of British Columbia; Sight Research UK; Strong; Koninklijk Nederlands Instituut voor Onderzoek der Zee; National Science Foundation","keywords":"Geotraces; Computer science; Data quality; Metadata; NetCDF; Data element; Database; Geology; Service (business); Oceanography; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002774391,0.001545023,0.001278661,0.006841344,0.0008579828,0.004886067,0.003140965,0.001529089,0.1290072],"category_scores_gemma":[0.0169142,0.0008576428,0.001327661,0.01170679,0.0005359544,0.005237751,0.003660766,0.001809387,0.174837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002007743,"about_ca_system_score_gemma":0.004678513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.038973,"about_ca_topic_score_gemma":0.02452204,"domain_scores_codex":[0.9971157,0.0003247353,0.0004608993,0.0004233053,0.001347036,0.0003283511],"domain_scores_gemma":[0.9914342,0.0009996126,0.0004581486,0.001923754,0.004752199,0.0004321237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001164751,0.00001595823,0.001273826,0.0003233649,0.0000265774,0.00004658727,0.00005461417,0.0006217897,0.0003563374,0.003054261,0.9821894,0.011921],"study_design_scores_gemma":[0.00004965622,0.000009943384,0.002030506,0.0001346492,0.00001435835,0.00003779527,0.00007804833,0.0005416112,0.0008501426,0.002491723,0.9937219,0.00003957437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003694428,0.00007984824,0.00204171,0.0001968675,0.0001127515,0.00005893241,0.9813461,0.005760362,0.01003396],"genre_scores_gemma":[0.001102425,0.00007639729,0.001777916,0.0000741733,0.00002432862,0.0001177993,0.9924493,0.001563464,0.002814213],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1290072,"threshold_uncertainty_score":0.4315721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02404959161957046,"score_gpt":0.2643189691485318,"score_spread":0.2402693775289613,"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."}}