{"id":"W4398937251","doi":"10.7910/dvn/qi2t9a/9otx0p","title":"20181105-icews-events.zip","year":2018,"lang":"ru","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":[0.001008887,0.0009697534,0.000731925,0.0003127929,0.0007216646,0.0003957585,0.002667766,0.0005199735,0.3117547],"category_scores_gemma":[0.0001496225,0.0009321604,0.0002458667,0.0003238287,0.000512992,0.001311934,0.001056869,0.0007585959,0.8473538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007860466,"about_ca_system_score_gemma":0.0000925831,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008616711,"about_ca_topic_score_gemma":0.001758835,"domain_scores_codex":[0.9945179,0.0003270529,0.000825509,0.001752224,0.001299293,0.00127803],"domain_scores_gemma":[0.9949387,0.0001790348,0.0005296785,0.003607668,0.00003113001,0.0007137995],"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":[0.0001398661,0.000195242,0.007459731,0.0002444525,0.0002319835,0.0002465735,0.00002986962,0.00003568341,0.000002987587,0.000005215284,0.9891495,0.002258895],"study_design_scores_gemma":[0.0007135632,0.0004934253,0.02076402,0.0002805541,0.0004522376,0.00002707256,0.0001841346,0.0001184218,0.00001448796,0.00002592997,0.9758777,0.001048429],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001117922,0.00001839844,0.00002563986,0.00002111767,0.007811627,0.0006272297,0.9876098,0.00007998029,0.002688303],"genre_scores_gemma":[0.0007149085,0.004498227,0.0008480477,0.0006412442,0.00279285,0.0000110297,0.9845712,0.0000308079,0.005891652],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5355991,"threshold_uncertainty_score":0.9993129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771500094721366,"score_gpt":0.2210652964322111,"score_spread":0.2033502954849974,"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."}}