{"id":"W4205844968","doi":"10.31234/osf.io/scg59","title":"The Emperor Has No Blanket!","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Charles Phelps Taft Research Center; Social Sciences and Humanities Research Council of Canada; Canada Research Chairs; University of Cincinnati","keywords":"Emperor; Blanket; Construct (python library); Work (physics); Computer science; History; Engineering; Archaeology; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001175316,0.0002231791,0.0002203085,0.00004544081,0.000611646,0.0009042092,0.003478087,0.0001304637,0.000366448],"category_scores_gemma":[0.00005828579,0.0001367624,0.0001954257,0.0001249879,0.00007030327,0.00007391102,0.005986466,0.0008306244,0.0001578032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005608588,"about_ca_system_score_gemma":0.0003176575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007968763,"about_ca_topic_score_gemma":0.00001372686,"domain_scores_codex":[0.9980564,0.0003345037,0.0002526805,0.0006542816,0.0003776078,0.0003245785],"domain_scores_gemma":[0.9974773,0.0002408252,0.0001150616,0.002000025,0.00007757697,0.00008922246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005427374,0.00003715204,0.00001324336,0.00002689567,0.00006029939,0.00002466872,0.0006686701,0.00004584726,0.00004712195,0.6599727,0.1256923,0.2134057],"study_design_scores_gemma":[0.00009307438,0.00003576362,0.00009434718,0.00001071467,0.000008882704,0.000009208361,0.000008698605,0.03889305,0.00008373537,0.2422035,0.71823,0.0003290211],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004668524,0.0004667084,0.8819264,0.007046542,0.003232951,0.0002403672,0.000005391604,0.0002251823,0.1068098],"genre_scores_gemma":[0.002483743,0.0001775975,0.9499096,0.001883008,0.0003224225,0.0001613219,0.000006709836,0.00002073782,0.04503484],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5925377,"threshold_uncertainty_score":0.871931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100523760294035,"score_gpt":0.2899730330086224,"score_spread":0.248967795405682,"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."}}