{"id":"W4245505697","doi":"10.1007/978-3-540-49127-9_7","title":"Linear Prediction","year":2007,"lang":"en","type":"book-chapter","venue":"Springer handbooks","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Linear prediction; Computer science; Context (archaeology); Linear model; Value (mathematics); Mathematics; Speech recognition; Machine learning; Geography","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":[0.000254033,0.0003096368,0.0002647794,0.0002557519,0.0001538178,0.0001533117,0.0006682564,0.000348244,0.00008648144],"category_scores_gemma":[0.00001165811,0.000305162,0.0001465057,0.00003272236,0.00006322329,0.0002102074,0.0002850942,0.0004926285,0.0005367394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007879976,"about_ca_system_score_gemma":0.0001199006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000207753,"about_ca_topic_score_gemma":0.000006987823,"domain_scores_codex":[0.9983071,0.000004469314,0.0003233452,0.0005789332,0.0004401093,0.000346049],"domain_scores_gemma":[0.9988778,0.00002834068,0.0001892852,0.0006455183,0.0001101216,0.0001488818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002167764,0.00002657614,0.00009873033,0.0001670887,0.0001471042,0.0003173605,0.0003739655,0.0000136912,0.002199989,0.09777892,0.004021033,0.8948339],"study_design_scores_gemma":[0.0003908789,0.0001060006,0.00005430973,0.0008772606,0.00003734013,0.0000619491,0.000001361399,0.0004792129,0.06598378,0.02970421,0.9016256,0.0006780705],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001655168,0.00144548,0.2859059,0.00005277783,0.0008600508,0.000117782,0.00000410422,0.0004369417,0.7111604],"genre_scores_gemma":[0.0005496323,0.0001882169,0.102477,0.0006638786,0.001794237,0.000006212326,0.00001017313,0.00008394861,0.8942267],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8976046,"threshold_uncertainty_score":0.99994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0367839464024551,"score_gpt":0.2490654939417637,"score_spread":0.2122815475393086,"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."}}