{"id":"W2553500230","doi":"10.1121/1.4970164","title":"Articulatory setting as global coarticulation: Simulation, acoustics, and perception","year":2016,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Phonetics and Phonology Research","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of British Columbia","funders":"","keywords":"Coarticulation; Perception; Computer science; Speech recognition; Context (archaeology); Set (abstract data type); Cognitive psychology; Psychology; Linguistics; Vowel","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":[0.000507329,0.0004604626,0.000313188,0.0003595983,0.0003056857,0.001823651,0.0008224456,0.0009575703,0.003806244],"category_scores_gemma":[0.002030174,0.0003263558,0.0005935025,0.0002667593,0.002306381,0.001651773,0.001030536,0.0007818767,0.0004132483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000471925,"about_ca_system_score_gemma":0.0004643547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00278472,"about_ca_topic_score_gemma":0.001672845,"domain_scores_codex":[0.9997513,0.0001250325,0.00000842872,0.00004904266,0.00004774722,0.00001841806],"domain_scores_gemma":[0.999671,0.0001904071,0.00002343467,0.00005484858,0.00001998436,0.00004022536],"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":[0.000433461,0.000122434,0.004870573,0.0004128925,0.0001803436,0.0005670847,0.004683116,0.5746467,0.06818993,0.271389,0.002520816,0.07198368],"study_design_scores_gemma":[0.00006857123,0.0001386756,0.005861736,0.00008870274,0.00004213438,0.0002951535,0.0005642536,0.7350218,0.004713571,0.2462963,0.006797879,0.0001111722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3654877,0.002173764,0.5822924,0.002825996,0.0002571513,0.000100844,0.0002482906,0.001159613,0.04545416],"genre_scores_gemma":[0.9577699,0.0004944535,0.03974983,0.0001227707,0.00002806901,0.00006382337,0.00006340494,0.0001152139,0.001592589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003806244,"threshold_uncertainty_score":0.0127331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774582335815041,"score_gpt":0.3361942437888175,"score_spread":0.3184484204306671,"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."}}