{"id":"W1650801579","doi":"10.48550/arxiv.1412.1841","title":"Exemplar Dynamics and Sound Merger in Language","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Phonetics and Phonology Research","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Merge (version control); Utterance; Contrast (vision); Pronunciation; Computer science; Vowel; Linguistics; Word (group theory); Diphthong; Vowel harmony; Speech recognition; Natural language processing; 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":[0.0006215338,0.0003109417,0.00058555,0.0007870155,0.0008636992,0.001760786,0.001781091,0.001577897,0.004487279],"category_scores_gemma":[0.003541605,0.0004625136,0.0007724705,0.0004078242,0.002089446,0.003617586,0.001999972,0.001137429,0.0004465271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001675211,"about_ca_system_score_gemma":0.0006160309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004908009,"about_ca_topic_score_gemma":0.002352851,"domain_scores_codex":[0.9997455,0.00005774318,0.000009717557,0.00005333012,0.00007670191,0.0000568266],"domain_scores_gemma":[0.9990174,0.0004215207,0.000167697,0.00009997109,0.0001393534,0.0001540692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005003126,0.00005425256,0.002048542,0.00004569657,0.00002703525,0.0004060705,0.001038177,0.1473607,0.008493282,0.8329687,0.0005861325,0.006921567],"study_design_scores_gemma":[0.00001418028,0.00002892103,0.0008297699,0.000007394276,0.000008463636,0.0001839133,0.00016594,0.7253794,0.0006522594,0.2719053,0.0008010142,0.00002334791],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5470284,0.0006170321,0.4276765,0.00218086,0.00007120455,0.00003908033,0.0001067635,0.0003185786,0.02196152],"genre_scores_gemma":[0.9738429,0.0002053353,0.01927591,0.0001065388,0.00003333637,0.00004505518,0.00005391098,0.00006682848,0.006370111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004908009,"threshold_uncertainty_score":0.01501143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06719930039472412,"score_gpt":0.251968910007162,"score_spread":0.1847696096124379,"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."}}