{"id":"W2965108857","doi":"","title":"Probability Distillation: A Caveat and Alternatives.","year":2019,"lang":"en","type":"article","venue":"Uncertainty in Artificial Intelligence","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal","funders":"","keywords":"Computer science; Distillation; Reliability engineering; Environmental science; Engineering; Chemistry; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003410355,0.000130168,0.0001611506,0.0000836004,0.00006463488,0.0001532981,0.0004955638,0.00005043863,0.00007388305],"category_scores_gemma":[0.0001174937,0.0001110756,0.00002803848,0.0003248067,0.00008898039,0.000461926,0.0003365756,0.0001428655,0.0001164704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006845067,"about_ca_system_score_gemma":0.00005222094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004697556,"about_ca_topic_score_gemma":0.0002487921,"domain_scores_codex":[0.9986374,0.0000696213,0.0003178781,0.0005172344,0.000222731,0.0002351732],"domain_scores_gemma":[0.9990624,0.0002250672,0.00007070613,0.0004990992,0.00006804581,0.00007466533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003428028,0.0001203646,0.006470961,0.00003415181,0.000005474431,0.00001775319,0.002074169,0.02037372,0.0006115233,0.5514335,0.00003080825,0.4187933],"study_design_scores_gemma":[0.00003450096,0.00006894036,0.003623132,0.00005477153,9.724118e-7,0.000005082089,0.0001004364,0.7738218,0.001393919,0.2199317,0.0007846065,0.00018014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3980497,0.0001320586,0.5981479,0.000775979,0.00056219,0.0004998865,0.000008794048,0.00009303798,0.001730538],"genre_scores_gemma":[0.9884775,0.00002872463,0.01127921,0.00008848647,0.00004462494,0.00001222153,0.000004594373,0.000004209413,0.00006040962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7534481,"threshold_uncertainty_score":0.4529531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04868565856059613,"score_gpt":0.2873961231225094,"score_spread":0.2387104645619132,"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."}}