{"id":"W4393599341","doi":"10.5281/zenodo.1407117","title":"Fine Fuel Moisture Code - ERA-Interim","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Interim; Code (set theory); Moisture; Environmental science; Waste management; Computer science; Geography; Engineering; Meteorology; Programming language; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003969276,0.000329872,0.0003505558,0.000306733,0.0007145493,0.001065217,0.00127876,0.0002557574,0.02753814],"category_scores_gemma":[0.0002304507,0.000343704,0.0001057977,0.0003701772,0.0001061854,0.0001914902,0.0005396448,0.0005653407,0.02587538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001941968,"about_ca_system_score_gemma":0.000003665111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004013299,"about_ca_topic_score_gemma":0.000008165328,"domain_scores_codex":[0.9980365,0.0002190619,0.000435179,0.0004439064,0.0004376302,0.000427748],"domain_scores_gemma":[0.9983385,0.00002202371,0.0001194653,0.0008837395,0.0004193542,0.0002169413],"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":[0.00002868191,0.00003668198,9.293426e-8,0.0002906176,0.0001062288,0.0000147294,0.00008299093,0.0004648282,0.0002463847,0.00003518426,0.99466,0.004033614],"study_design_scores_gemma":[0.0005134057,0.0001268492,0.00003962043,0.00009126688,0.00003316455,0.00006515545,0.00002159545,0.002050259,0.00001807364,0.00002154716,0.9966847,0.0003344117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006726672,0.0002268865,0.0007310548,0.0001133626,0.0006052286,0.0005480596,0.9575052,0.001550903,0.03865207],"genre_scores_gemma":[0.009359024,0.00014265,0.00002830948,0.00006792767,0.0008551378,9.970358e-8,0.9868602,0.001755268,0.0009313567],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03772072,"threshold_uncertainty_score":0.9999717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02323974080527793,"score_gpt":0.2414397806949626,"score_spread":0.2182000398896847,"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."}}