{"id":"W2266004465","doi":"","title":"Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning .","year":2012,"lang":"en","type":"article","venue":"Cambridge University Engineering Department Publications Database","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Bayesian probability; Artificial intelligence; Unsupervised learning; Machine learning; Pattern recognition (psychology)","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":[0.01999736,0.001564529,0.001900945,0.002914481,0.001195272,0.002641392,0.002737408,0.003446374,0.003957292],"category_scores_gemma":[0.09070653,0.001025606,0.001163318,0.001968679,0.001515087,0.004346974,0.003375198,0.002813035,0.001468758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002301137,"about_ca_system_score_gemma":0.002590451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01676473,"about_ca_topic_score_gemma":0.02887682,"domain_scores_codex":[0.9890786,0.00685576,0.0005581484,0.001001484,0.002139174,0.0003667983],"domain_scores_gemma":[0.9154897,0.07288998,0.001446045,0.003313912,0.005910394,0.0009499818],"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":[0.003011417,0.0006119941,0.009130837,0.00071348,0.0008828735,0.00009317818,0.0002763461,0.4920037,0.001915765,0.0247553,0.01801523,0.44859],"study_design_scores_gemma":[0.0001264657,0.0001877136,0.001214376,0.00005166132,0.00009987978,0.00004830792,0.00008349599,0.9768116,0.001461021,0.01872543,0.001165204,0.00002484592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1071288,0.007174073,0.8699629,0.002042221,0.0003117793,0.0003099954,0.001609698,0.003231002,0.008229575],"genre_scores_gemma":[0.5501061,0.001760301,0.4318988,0.0006892397,0.0005108148,0.0003659706,0.006759537,0.001028464,0.006880773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01999736,"threshold_uncertainty_score":0.1057574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08170086113538608,"score_gpt":0.2562536995249276,"score_spread":0.1745528383895415,"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."}}