{"id":"W4398880264","doi":"10.7910/dvn/qi2t9a/qsrwrm","title":"20181003-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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001041719,0.002417287,0.001410097,0.003872403,0.0007541067,0.003107643,0.002811375,0.00158496,0.1836987],"category_scores_gemma":[0.005584346,0.001016903,0.001048972,0.007395327,0.0004960154,0.002167912,0.00236087,0.00141954,0.2106087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001373403,"about_ca_system_score_gemma":0.001603501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0162325,"about_ca_topic_score_gemma":0.02008441,"domain_scores_codex":[0.9991941,0.00008534219,0.00009360883,0.0002543606,0.0001760085,0.0001965919],"domain_scores_gemma":[0.9977633,0.0005320223,0.000205399,0.0007344303,0.0004174243,0.0003474839],"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":[0.00005486458,0.0000104313,0.0003193724,0.0001884116,0.00001078842,0.000009354269,0.00001296244,0.0001383144,0.00005091925,0.0003784627,0.9976489,0.001177351],"study_design_scores_gemma":[0.0003156229,0.00001294923,0.00216731,0.000103774,0.00001335736,0.00002321092,0.00004233083,0.0006276299,0.0003767067,0.001219151,0.9950771,0.00002087259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007626675,0.00001550452,0.00004952545,0.00004102153,0.00001823433,0.000008127,0.9978072,0.001078177,0.0009060075],"genre_scores_gemma":[0.0003400764,0.00002358295,0.0001327358,0.00002839396,0.00001016967,0.00003948772,0.9985008,0.0003519483,0.0005728752],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8163013,"threshold_uncertainty_score":0.6145333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767793328116785,"score_gpt":0.2210115568927736,"score_spread":0.2033336236116057,"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."}}