{"id":"W4398901720","doi":"10.7910/dvn/qi2t9a/fgwei8","title":"20190222-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":"Event (particle physics); Physics","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":[0.001144065,0.0009680556,0.0008291638,0.0003176898,0.0004373409,0.0003718682,0.002643967,0.0005175023,0.266473],"category_scores_gemma":[0.000151444,0.0009360494,0.0002783462,0.0002907241,0.0002132564,0.001403538,0.001021939,0.000979512,0.9191146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001171101,"about_ca_system_score_gemma":0.0001206778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006393478,"about_ca_topic_score_gemma":0.0005757826,"domain_scores_codex":[0.9941169,0.0003227456,0.0007972321,0.001736071,0.00180726,0.001219793],"domain_scores_gemma":[0.9947163,0.0002348949,0.000534381,0.003916318,0.00003253368,0.0005655431],"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":[0.0001332707,0.0001937693,0.009401632,0.000496114,0.0002459112,0.0002129258,0.00003342853,0.0004428135,0.000004019737,0.000004050886,0.9868744,0.001957636],"study_design_scores_gemma":[0.0008918761,0.0003320189,0.02012393,0.0002799641,0.0004404288,0.00002209052,0.0003189996,0.00023954,0.000008140442,0.000008449346,0.9762517,0.001082838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008609814,0.00003008561,0.00002189274,0.0000219481,0.008685941,0.0008670472,0.9857864,0.00005534416,0.003670361],"genre_scores_gemma":[0.001422956,0.005950314,0.00042498,0.0006814499,0.001155117,0.000009061669,0.9787729,0.00003202607,0.01155115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6526417,"threshold_uncertainty_score":0.999309,"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."}}