{"id":"W23587205","doi":"10.1186/1471-2458-13-346","title":"Listener deficits in hypokinetic dysarthria: Which cues are most important in speech segmentation?","year":2013,"lang":"en","type":"article","venue":"PhDT","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Canadian Institutes of Health Research; Cancer Research UK","keywords":"Dysarthria; Audiology; Psychology; Speech recognition; Segmentation; Communication; Computer science; Medicine; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000612453,0.0005150938,0.0004422948,0.0009957042,0.0002445471,0.001021041,0.0002379502,0.0005392493,0.007585055],"category_scores_gemma":[0.005265805,0.0001315237,0.0001652563,0.000372553,0.0004720179,0.001469583,0.0006431183,0.0005078488,0.0006734402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002186005,"about_ca_system_score_gemma":0.0003188605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001994911,"about_ca_topic_score_gemma":0.003779537,"domain_scores_codex":[0.9996947,0.00004637449,0.00006209311,0.00006632072,0.00008641888,0.00004418873],"domain_scores_gemma":[0.9978092,0.0009551732,0.0007678444,0.00008446616,0.0002285714,0.0001546699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003152466,0.0007402434,0.6123771,0.0005842038,0.0002417401,0.01108677,0.0102739,0.0009624882,0.1800684,0.0009066305,0.001494918,0.1781111],"study_design_scores_gemma":[0.00002828665,0.0004031545,0.9823554,0.0001105666,0.0000753491,0.004534476,0.003399129,0.0006615861,0.00658052,0.001107577,0.0007111121,0.00003285467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992924,0.0003906307,0.001117227,0.0002818269,0.0000264209,0.00002370408,0.000198357,0.0000356688,0.005002112],"genre_scores_gemma":[0.9983178,0.0001554012,0.0005323383,0.00007865459,0.00001812832,0.000009274189,0.00009325687,0.000029498,0.0007655714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007585055,"threshold_uncertainty_score":0.02537453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393954156494697,"score_gpt":0.2637862736075304,"score_spread":0.2498467320425835,"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."}}