{"id":"W4285264466","doi":"10.2139/ssrn.4101003","title":"Regularizing Deep Text Models by Encouraging Competition","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Competition (biology); Computer science; Psychology; Data science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006548271,0.002334172,0.002427524,0.001845321,0.0013526,0.002965984,0.00366295,0.004813659,0.006995722],"category_scores_gemma":[0.03326687,0.001425187,0.001636201,0.001779453,0.001521105,0.00764446,0.005125025,0.007119928,0.003768848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357284,"about_ca_system_score_gemma":0.001810942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003786342,"about_ca_topic_score_gemma":0.008667234,"domain_scores_codex":[0.9961382,0.001707808,0.0002092174,0.001098941,0.0004789901,0.0003668743],"domain_scores_gemma":[0.9726611,0.02115288,0.0009541205,0.00228565,0.001871855,0.001074234],"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":[0.002495396,0.001138691,0.008576086,0.0007372939,0.0004863337,0.0003751951,0.0007336165,0.6501724,0.01324202,0.03927972,0.0476207,0.2351425],"study_design_scores_gemma":[0.00005515714,0.00009285207,0.0002211459,0.00001667557,0.00004145539,0.00003083069,0.00002668655,0.9792249,0.0009975563,0.01820972,0.001070371,0.00001263502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.18013,0.002484328,0.7945219,0.005140989,0.001095551,0.0002626944,0.001632924,0.006343233,0.008388477],"genre_scores_gemma":[0.8993648,0.0005843499,0.07442966,0.001404323,0.001199251,0.0004090524,0.003937785,0.001273262,0.01739757],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006995722,"threshold_uncertainty_score":0.03463095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008238387120771863,"score_gpt":0.2061809810508495,"score_spread":0.1979425939300777,"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."}}