{"id":"W2952393068","doi":"10.48550/arxiv.1302.6783","title":"Generating New Beliefs From Old","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Knowledge base; Computer science; Belief revision; Belief structure; Limiting; Entropy (arrow of time); Base (topology); Artificial intelligence; Epistemology; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.0001142458,0.0003437901,0.0003218449,0.000130009,0.0001573389,0.0003845592,0.002323824,0.0003635816,0.0001146088],"category_scores_gemma":[0.00002315646,0.0003948253,0.0001693601,0.0002913419,0.00004749489,0.0004308899,0.002216661,0.0007178271,0.0005412217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143141,"about_ca_system_score_gemma":0.000339298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004832783,"about_ca_topic_score_gemma":0.00006979857,"domain_scores_codex":[0.9979016,0.00009838259,0.000220916,0.001292334,0.0001040355,0.0003826932],"domain_scores_gemma":[0.9978001,0.00007670621,0.0002121991,0.001460251,0.0001293122,0.0003214269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004725358,0.00006211798,0.0006563074,0.00002500021,0.000115057,0.0001579957,0.0007213835,0.6963396,0.0003943948,0.2874034,0.005550667,0.008569336],"study_design_scores_gemma":[0.0001850437,0.00001835413,0.0001859986,0.00008995055,0.00002395159,0.000001114835,0.00001229048,0.8408142,0.0001690495,0.1578509,0.0002353815,0.0004137402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1822214,0.0001286325,0.8153074,0.0001846169,0.0006408168,0.0001233015,0.000008730835,0.0003280383,0.001057014],"genre_scores_gemma":[0.9530213,0.000128232,0.0391939,0.0004725468,0.0003772711,7.079645e-7,0.00002256667,0.00001944309,0.006764038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7761136,"threshold_uncertainty_score":0.9998504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09657510181953814,"score_gpt":0.1872069595592946,"score_spread":0.09063185773975642,"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."}}