{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001102451,0.001987036,0.00120332,0.003841348,0.0008301625,0.003240305,0.002559434,0.001556252,0.2538363],"category_scores_gemma":[0.005923082,0.00111972,0.0009519749,0.007409797,0.0004616769,0.002330064,0.002282768,0.00139704,0.2791905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001581635,"about_ca_system_score_gemma":0.001546299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0166823,"about_ca_topic_score_gemma":0.02072907,"domain_scores_codex":[0.9992255,0.00008243786,0.0001028113,0.0002433843,0.0001571226,0.000188759],"domain_scores_gemma":[0.9970539,0.0006892937,0.0002618303,0.0009243691,0.0005665053,0.0005041421],"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":[0.00004992782,0.00001000899,0.0002976569,0.000179535,0.000008865536,0.000007239112,0.00001195347,0.0001008031,0.00006074717,0.0004125333,0.9978536,0.001007196],"study_design_scores_gemma":[0.0002648742,0.00001244865,0.002219139,0.000096925,0.00001143599,0.00001771012,0.00004149554,0.0003939632,0.0003827208,0.0009983798,0.9955385,0.00002232628],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005616836,0.00001129963,0.00004195346,0.00003944814,0.0000160601,0.000007621939,0.9977817,0.0009058357,0.001139897],"genre_scores_gemma":[0.0003287783,0.00002250319,0.0001353595,0.00004543169,0.00000956945,0.00003982,0.9981426,0.0004742469,0.0008016311],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7461637,"threshold_uncertainty_score":0.849167,"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."}}