{"id":"W2950599832","doi":"10.3390/app9112384","title":"Estimating Vocal Fold Contact Pressure from Raw Laryngeal High-Speed Videoendoscopy Using a Hertz Contact Model","year":2019,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute on Deafness and Other Communication Disorders; Comisión Nacional de Investigación Científica y Tecnológica","keywords":"Vocal folds; Kinematics; Stroboscope; Computer science; Collision; Acoustics; Kalman filter; Simulation; Physics; Artificial intelligence; Larynx; Optics; Surgery; Medicine","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":[0.0002668427,0.0004445505,0.0002923529,0.000621074,0.0001667461,0.0006225221,0.0004034367,0.000611864,0.0008635116],"category_scores_gemma":[0.0008630304,0.0002358822,0.0003955101,0.0003776498,0.0002037486,0.0005300816,0.0003814008,0.0003211434,0.0003626971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002479382,"about_ca_system_score_gemma":0.000483728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003574438,"about_ca_topic_score_gemma":0.003882907,"domain_scores_codex":[0.9998205,0.00002627746,0.000008982573,0.00004993315,0.00007547414,0.00001894311],"domain_scores_gemma":[0.9998287,0.00007767115,0.00002999345,0.00001821436,0.00003602923,0.0000094105],"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":[0.0003313363,0.0001689235,0.02320126,0.000303939,0.0001085685,0.0007305526,0.0003971684,0.4072365,0.2096104,0.002601878,0.001005842,0.3543037],"study_design_scores_gemma":[0.000005357797,0.00009944701,0.009123784,0.00001194959,0.00001882096,0.0002504443,0.00004817315,0.9781173,0.01120668,0.00042843,0.0006694354,0.0000202259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1411546,0.0002255168,0.856822,0.00005184679,0.00002310983,0.00005476395,0.0001320917,0.0004196074,0.001116552],"genre_scores_gemma":[0.8669171,0.0004693736,0.1305988,0.00003199737,0.00002412917,0.00009328162,0.0002499428,0.00005815466,0.00155716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003574438,"threshold_uncertainty_score":0.007107258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798129624081148,"score_gpt":0.2942975685244412,"score_spread":0.2663162722836297,"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."}}