{"id":"W4398853481","doi":"10.7910/dvn/qi2t9a/8dacns","title":"20190223-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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009760095,0.0009685832,0.0008299166,0.0003177104,0.0004359775,0.0003721253,0.002629286,0.0005176513,0.2652936],"category_scores_gemma":[0.0001494384,0.0009366879,0.0002786556,0.0002904286,0.0002132936,0.001403607,0.001021593,0.0009707974,0.9200743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001160108,"about_ca_system_score_gemma":0.0001198637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006235551,"about_ca_topic_score_gemma":0.0006954604,"domain_scores_codex":[0.9941182,0.0003170533,0.0007942428,0.001736608,0.001804993,0.001228931],"domain_scores_gemma":[0.994718,0.0002295484,0.0005325319,0.00391797,0.00003258022,0.0005693827],"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":[0.0001369706,0.0001936515,0.008054297,0.0004073421,0.0002465968,0.0002104487,0.00003703377,0.0004419296,0.000004237119,0.000004741471,0.9880547,0.002208052],"study_design_scores_gemma":[0.0009161263,0.0003320214,0.01767674,0.0002844001,0.0004415979,0.00002183537,0.0003777702,0.0002355123,0.000008574814,0.000008336352,0.9786108,0.001086248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007653133,0.00003479784,0.00001793756,0.00002164117,0.008635694,0.0008689967,0.9858696,0.00005541428,0.003730593],"genre_scores_gemma":[0.00138569,0.005876655,0.0004255202,0.0006749073,0.001138842,0.000008826783,0.9785086,0.00003205393,0.01194893],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6547807,"threshold_uncertainty_score":0.9993083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221141794566434,"score_gpt":0.2238465981211671,"score_spread":0.2016351801755027,"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."}}