{"id":"W4398919105","doi":"10.7910/dvn/qi2t9a/9d75xg","title":"20190225-icews-events.zip","year":2019,"lang":"ja","type":"dataset","venue":"Harvard Dataverse","topic":"Environmental Monitoring and Data Management","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00105753,0.001849681,0.0011635,0.003950267,0.000826097,0.003153371,0.002448133,0.001475709,0.2586565],"category_scores_gemma":[0.00588538,0.001058403,0.0008865006,0.007913111,0.0004356437,0.002269991,0.002169824,0.00133173,0.2591148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001678621,"about_ca_system_score_gemma":0.00169573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02144001,"about_ca_topic_score_gemma":0.0264733,"domain_scores_codex":[0.9992322,0.00007625033,0.0001010175,0.0002371007,0.0001555348,0.0001979395],"domain_scores_gemma":[0.996949,0.0007067272,0.0002990226,0.0009131276,0.0006232975,0.0005088183],"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":[0.0000452911,0.000009103982,0.0003333515,0.0001694689,0.000008476785,0.000006983048,0.00001258077,0.00009518648,0.00005546145,0.0004387115,0.9978428,0.0009825992],"study_design_scores_gemma":[0.0002390189,0.00001064716,0.002512011,0.00009910577,0.00001126269,0.00001610514,0.0000438891,0.0003485812,0.0003604619,0.0009698284,0.9953676,0.00002145646],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005148227,0.000009462379,0.00003485169,0.00003458502,0.00001418157,0.000006400955,0.9981261,0.0006478344,0.001075084],"genre_scores_gemma":[0.0003389503,0.0000210786,0.0001273289,0.00004311047,0.000009984898,0.00003705975,0.9981545,0.0004049529,0.0008631145],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7413435,"threshold_uncertainty_score":0.8652923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02225248818696623,"score_gpt":0.2238150774062341,"score_spread":0.2015625892192679,"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."}}