{"id":"W4398855468","doi":"10.7910/dvn/qi2t9a/fgzht5","title":"20190121-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":[0.001138715,0.002045146,0.001251358,0.004015679,0.0008664358,0.003319901,0.002612062,0.001610699,0.2578147],"category_scores_gemma":[0.006108033,0.001141648,0.0009600446,0.007881813,0.0004710251,0.002406549,0.002341605,0.001467091,0.2830297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001665799,"about_ca_system_score_gemma":0.001662411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0172097,"about_ca_topic_score_gemma":0.02125723,"domain_scores_codex":[0.999164,0.00008871716,0.0001113181,0.0002609976,0.000169784,0.000205225],"domain_scores_gemma":[0.9969333,0.0007199693,0.0002724761,0.0009440187,0.0005992401,0.0005309037],"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":[0.00004899758,0.00001019035,0.0002748839,0.0001852819,0.000008482924,0.000007104038,0.00001202858,0.00009790805,0.00006123839,0.0004198226,0.9979011,0.000972915],"study_design_scores_gemma":[0.0002631828,0.00001242804,0.002053722,0.00009801445,0.00001110091,0.00001739654,0.00004176788,0.0003698896,0.0003854862,0.0009563636,0.9957687,0.00002198774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005221728,0.00001101993,0.00004070334,0.00003755905,0.0000153758,0.00000767932,0.9978861,0.0008364258,0.001112971],"genre_scores_gemma":[0.0003015911,0.00002179323,0.0001295547,0.00004387792,0.000008943412,0.00003999815,0.9982272,0.0004441681,0.0007828044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7421854,"threshold_uncertainty_score":0.862476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240781757523443,"score_gpt":0.2243771786775106,"score_spread":0.2019693611022761,"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."}}