{"id":"W6966353176","doi":"10.48448/8k6y-dv50","title":"Personalized Lip Reading: Adapting to Your Unique Lip Movements with Vision and Language","year":2025,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Vocabulary; Sentence; Adaptation (eye); Reading (process); Language model; Sensory cue; Spoken language","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":[0.0006930346,0.001446979,0.0009771897,0.0006695929,0.0002239088,0.0008337946,0.001381917,0.001020905,0.003353206],"category_scores_gemma":[0.001954052,0.0003141039,0.00101644,0.0003226804,0.0003852445,0.001400118,0.001426477,0.001242565,0.00415334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003176117,"about_ca_system_score_gemma":0.0003586503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002230672,"about_ca_topic_score_gemma":0.003818713,"domain_scores_codex":[0.9993973,0.0001032826,0.00002713969,0.0002891493,0.0001269337,0.00005624167],"domain_scores_gemma":[0.9995245,0.0001613523,0.00003123784,0.000137633,0.0001081127,0.00003728373],"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":[0.0006725451,0.0002429539,0.003025354,0.0004265459,0.0002029484,0.0005132869,0.0002370909,0.02630625,0.1562357,0.0008589398,0.01885575,0.7924227],"study_design_scores_gemma":[0.0001326176,0.0006410041,0.01377716,0.0001052444,0.0002703998,0.001926551,0.0003796561,0.8080214,0.1509201,0.003898165,0.01975034,0.0001772528],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1853828,0.003949941,0.7551236,0.0005578986,0.0007853688,0.0004310901,0.003323207,0.0391018,0.01134438],"genre_scores_gemma":[0.6553053,0.001623779,0.3117284,0.0009480779,0.0003316249,0.0003455731,0.01037356,0.001584373,0.01775929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003353206,"threshold_uncertainty_score":0.01121759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812726593670597,"score_gpt":0.3267287562833585,"score_spread":0.3086014903466525,"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."}}