{"id":"W2100002341","doi":"","title":"Replicated Softmax: an Undirected Topic Model","year":2009,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Topic Modeling","field":"Computer Science","cited_by":442,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Latent Dirichlet allocation; Softmax function; Computer science; Graphical model; Inference; Artificial intelligence; Topic model; Latent variable; Undirected graph; Dirichlet distribution; Theoretical computer science; Data mining; Machine learning; Algorithm; Graph; Deep learning; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002458199,0.0001297607,0.0001482047,0.0001365825,0.0001994962,0.0008681432,0.0005798952,0.00008110482,8.156398e-7],"category_scores_gemma":[0.00003721239,0.0001163407,0.00002607995,0.0003528797,0.000009940114,0.006639922,0.00003627888,0.0001267453,0.00002065439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000605917,"about_ca_system_score_gemma":0.00009210513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002282958,"about_ca_topic_score_gemma":6.288028e-7,"domain_scores_codex":[0.9986908,0.0000341144,0.0005033295,0.0002048129,0.0003051104,0.0002618614],"domain_scores_gemma":[0.9989194,0.000008337716,0.0002426827,0.0004939411,0.0002319308,0.0001037573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008846892,0.00004689192,0.0001224538,0.0001649738,0.000004717107,0.000002045926,0.004878316,0.360736,0.001607439,0.02805504,0.0006336647,0.6037396],"study_design_scores_gemma":[0.0001511588,0.00003798939,0.0002501727,0.00002938705,0.000001919104,0.00002937775,0.00004052312,0.9978875,0.0002400599,0.0006462719,0.0005453687,0.0001402901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04927099,0.00006550938,0.9446685,0.0007851637,0.0002516204,0.0002264909,0.000001026517,0.001003862,0.003726852],"genre_scores_gemma":[0.987062,0.000001248079,0.01162013,0.00102461,0.00006098294,0.00001404779,0.00001623015,0.000003750854,0.0001970434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.937791,"threshold_uncertainty_score":0.8371525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266415990600878,"score_gpt":0.2715287157289674,"score_spread":0.2388645558229586,"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."}}