{"id":"W4394159867","doi":"10.6084/m9.figshare.24921345","title":"ARBT raw data FACETS.xlsx","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Raw data; Computer science; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001989741,0.0004086362,0.0004550165,0.000149147,0.0001641283,0.0008485934,0.01172157,0.0003732095,0.008103464],"category_scores_gemma":[0.0009888714,0.0003942565,0.0001062675,0.0007135239,0.000005948571,0.0003493017,0.00633533,0.0005749121,0.1759595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004175954,"about_ca_system_score_gemma":0.0003024683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001353595,"about_ca_topic_score_gemma":0.00005544973,"domain_scores_codex":[0.9970533,0.0001195464,0.0004143158,0.001230795,0.00061799,0.0005641097],"domain_scores_gemma":[0.9936003,0.0003172573,0.0003351721,0.005458108,0.0001108035,0.0001783441],"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":[4.946468e-7,0.00001773667,8.701069e-8,0.0003670784,0.00003638841,0.0001334725,0.000007073443,0.000098532,7.476282e-8,0.000004937964,0.9989124,0.0004217188],"study_design_scores_gemma":[0.0001166139,0.00002050989,0.00001807762,0.002176581,0.000007903167,0.00002586498,0.000001660496,0.007701295,7.575738e-7,0.00002226422,0.9894533,0.0004551397],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.955867e-8,0.0003092218,0.0002254482,0.0001173403,0.00127161,0.0002837979,0.9969215,0.0006364404,0.0002346643],"genre_scores_gemma":[0.000004323149,0.000008890299,0.0001024829,0.0002139235,0.0007008411,0.000063697,0.9981652,0.00002507495,0.000715511],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1678561,"threshold_uncertainty_score":0.9998509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563565549687996,"score_gpt":0.3265810582342838,"score_spread":0.1702245032654842,"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."}}