{"id":"W4398946734","doi":"10.7910/dvn/qi2t9a/r1sqcc","title":"20190607-icews-events.zip","year":2019,"lang":"es","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":[0.0009738076,0.001910792,0.001192591,0.003494064,0.0007594245,0.002874303,0.002295517,0.001431571,0.2537356],"category_scores_gemma":[0.004917837,0.0009902333,0.0008485674,0.007229926,0.000417013,0.002126039,0.002095141,0.001287304,0.2575367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580695,"about_ca_system_score_gemma":0.001600369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02203271,"about_ca_topic_score_gemma":0.02644298,"domain_scores_codex":[0.9993076,0.00006667541,0.00008550138,0.0002116583,0.0001447658,0.0001837606],"domain_scores_gemma":[0.9975963,0.0005491784,0.0002335221,0.0006886716,0.000531701,0.0004005781],"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":[0.00004325236,0.000008361711,0.0002998046,0.0001552054,0.000007901715,0.000006135467,0.00001122204,0.00009632944,0.00004841855,0.0003974035,0.9979055,0.001020506],"study_design_scores_gemma":[0.0002377819,0.000009962124,0.002321737,0.0000982393,0.00001070955,0.00001411912,0.00004130083,0.0003734575,0.0003377403,0.0009773385,0.9955577,0.00001988644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004756748,0.000008500487,0.00003353333,0.00003274582,0.00001318881,0.000006247551,0.9982547,0.0005400046,0.001063425],"genre_scores_gemma":[0.0003094845,0.00001964798,0.0001210213,0.00003848385,0.000009059849,0.00003679432,0.9982545,0.0003156927,0.0008952148],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7462645,"threshold_uncertainty_score":0.84883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02089925475684276,"score_gpt":0.225447145825929,"score_spread":0.2045478910690862,"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."}}