{"id":"W1580822516","doi":"","title":"Imposing Hierarchical Browsing Structures onto Spoken Documents","year":2010,"lang":"en","type":"article","venue":"NPARC","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; National Research Council Canada","funders":"","keywords":"Computer science; Baseline (sea); Dynamic programming; Hierarchical database model; Scheme (mathematics); Hierarchical organization; Artificial intelligence; Data mining; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002622637,0.0009937586,0.001233107,0.0008146868,0.001145651,0.001813984,0.001761938,0.001532816,0.005001141],"category_scores_gemma":[0.01391328,0.000994947,0.0009214849,0.001537807,0.001249115,0.005489865,0.003050119,0.002755612,0.002167113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005622805,"about_ca_system_score_gemma":0.001876264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004820071,"about_ca_topic_score_gemma":0.01030634,"domain_scores_codex":[0.9971876,0.00108042,0.0001347004,0.000699996,0.0006903341,0.0002069816],"domain_scores_gemma":[0.9897475,0.006096872,0.0007143109,0.002368493,0.0007955016,0.0002773095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001045364,0.0005004663,0.004622479,0.0009684996,0.0001224721,0.0009264917,0.002895551,0.1241903,0.1031535,0.03129497,0.008023974,0.7222559],"study_design_scores_gemma":[0.0001204407,0.0006080507,0.003553736,0.0001422407,0.000125404,0.0009623229,0.001797233,0.8557862,0.07551377,0.04496232,0.01628637,0.000141838],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08424263,0.0003054313,0.906381,0.0001966737,0.00003964631,0.0001116289,0.0002870841,0.005314879,0.003120953],"genre_scores_gemma":[0.4352497,0.0005061151,0.5530049,0.0001544658,0.0001042949,0.0002319547,0.002246022,0.0008600593,0.007642454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005001141,"threshold_uncertainty_score":0.01673043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006584873957553026,"score_gpt":0.2714422880427332,"score_spread":0.2648574140851802,"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."}}