{"id":"W4393581249","doi":"10.5281/zenodo.7094972","title":"openstack-24hr","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0008937926,0.0028054,0.00124152,0.002363327,0.0008529311,0.001536263,0.00199494,0.001682239,0.0121141],"category_scores_gemma":[0.003775019,0.0006107192,0.001192092,0.003404869,0.0005546385,0.001625761,0.00157485,0.00150866,0.03050597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009020559,"about_ca_system_score_gemma":0.00127019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01332544,"about_ca_topic_score_gemma":0.02138958,"domain_scores_codex":[0.9982475,0.0001911504,0.0001809691,0.0005627785,0.0005586663,0.0002589407],"domain_scores_gemma":[0.9977105,0.0003189386,0.0001808492,0.0009175735,0.0006411355,0.0002309495],"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":[0.0004497379,0.0001497455,0.00361885,0.0006698194,0.00007688622,0.0001055625,0.00008447046,0.001729627,0.001244677,0.0005552298,0.980977,0.01033844],"study_design_scores_gemma":[0.0007899409,0.0003200929,0.04700837,0.0003658948,0.00009090712,0.0006281846,0.0003536006,0.01221269,0.00624172,0.003291212,0.9285001,0.0001973397],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00519546,0.0002831316,0.0003605911,0.0001208087,0.0001289343,0.00004913549,0.9870198,0.005443941,0.00139824],"genre_scores_gemma":[0.003989416,0.00005709207,0.000366205,0.00004142235,0.00001582879,0.00006950274,0.9948085,0.0001695179,0.0004825342],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01332544,"threshold_uncertainty_score":0.04052573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07505209744837793,"score_gpt":0.2264136102568353,"score_spread":0.1513615128084574,"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."}}