{"id":"W4398924840","doi":"10.7910/dvn/qi2t9a/8ynfmk","title":"20190622-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":[0.001054105,0.001863867,0.001157532,0.003920875,0.0008348118,0.003156955,0.002455248,0.001484882,0.2595082],"category_scores_gemma":[0.005844223,0.001067365,0.0008819271,0.007789903,0.0004336204,0.002314247,0.002191058,0.001343034,0.2646884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001657159,"about_ca_system_score_gemma":0.001672333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02048042,"about_ca_topic_score_gemma":0.0258325,"domain_scores_codex":[0.9992372,0.00007520973,0.0001010349,0.0002372266,0.0001554503,0.0001939412],"domain_scores_gemma":[0.9969578,0.0007037173,0.0002949134,0.0009134086,0.0006194831,0.0005107785],"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":[0.0000455595,0.00000928399,0.0003253248,0.0001662104,0.000008150696,0.000006892218,0.00001241745,0.00009122207,0.00005606656,0.0004272639,0.9978833,0.0009682825],"study_design_scores_gemma":[0.0002401229,0.00001068434,0.002402717,0.00009661547,0.00001081214,0.00001619721,0.00004339913,0.0003446743,0.0003540042,0.0009616789,0.9954978,0.00002110259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005125237,0.000009305361,0.00003485193,0.00003497152,0.00001408171,0.00000645023,0.9980995,0.0006608334,0.001088848],"genre_scores_gemma":[0.0003329529,0.00002057853,0.0001289962,0.00004281427,0.000009808003,0.00003734366,0.9981389,0.0004121522,0.0008765349],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7404917,"threshold_uncertainty_score":0.8681415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02230719661884454,"score_gpt":0.2239312664737648,"score_spread":0.2016240698549203,"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."}}