{"id":"W4398862435","doi":"10.7910/dvn/vvxwzo/i5tcrs","title":"p02.arff","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Memorial University of Newfoundland","funders":"","keywords":"Replication (statistics); Authentication (law); Computer science; Dynamics (music); Internet privacy; Computer security; Psychology; Medicine; Virology","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":[0.0003333488,0.000287806,0.0003616527,0.0002234963,0.00008370708,0.0004546079,0.003621428,0.0002559457,0.005893201],"category_scores_gemma":[0.00008062751,0.000277714,0.0001298169,0.0002564728,0.00003884372,0.0006171995,0.00112429,0.0003435222,0.6140006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005927435,"about_ca_system_score_gemma":0.0001741994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000152698,"about_ca_topic_score_gemma":0.00003989868,"domain_scores_codex":[0.9978924,0.0001261668,0.0003699147,0.0007198317,0.0005531735,0.0003385597],"domain_scores_gemma":[0.9952309,0.00007151052,0.0002367646,0.004218455,0.00008258613,0.0001598248],"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":[0.000001816321,0.00005284437,0.000001914426,0.0001047039,0.00003219544,0.00002627213,0.0003140257,2.385437e-7,0.000002930559,0.000495289,0.9988611,0.0001067062],"study_design_scores_gemma":[0.0002357408,0.00002350353,0.00001355952,0.00005744271,0.00002558173,0.00002206913,0.0000134792,0.001822346,0.000005947479,0.00005776341,0.9973958,0.0003267806],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002816633,0.000001668682,0.002302088,0.0000253964,0.002695353,0.0003172327,0.9942839,0.0001082735,0.0002633309],"genre_scores_gemma":[0.00003767339,0.00007901712,0.0003132147,0.0008254558,0.0001768116,0.00001778549,0.9968891,0.0000117877,0.00164911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6081074,"threshold_uncertainty_score":0.9999675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449130624713794,"score_gpt":0.2529910260622441,"score_spread":0.2284997198151061,"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."}}