{"id":"W2262989991","doi":"10.1080/15475441.2015.1073153","title":"How Transitional Probabilities and the Edge Effect Contribute to Listeners’ Phonological Bootstrapping Success","year":2016,"lang":"en","type":"article","venue":"Language Learning and Development","topic":"Language Development and Disorders","field":"Psychology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Speech segmentation; Utterance; Computer science; Phonotactics; Speech recognition; Bootstrapping (finance); Natural language processing; Text segmentation; Salient; Segmentation; Artificial intelligence; Natural language; Natural (archaeology); Phonology; Linguistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002262874,0.0003213722,0.0003575024,0.0006258872,0.0002863994,0.001997619,0.0004929947,0.000792487,0.004083609],"category_scores_gemma":[0.03037829,0.0006511661,0.0002276813,0.0002876606,0.001257977,0.002253177,0.00147409,0.001043982,0.0006182159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001687575,"about_ca_system_score_gemma":0.0003767176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009190377,"about_ca_topic_score_gemma":0.0008478117,"domain_scores_codex":[0.9989359,0.0003234885,0.00006244161,0.0002978832,0.0002229364,0.0001574493],"domain_scores_gemma":[0.979584,0.01609253,0.001470584,0.001268728,0.0007483421,0.000835866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003515999,0.0005289765,0.3685746,0.0003297999,0.0002777586,0.001607701,0.01002539,0.007927293,0.38421,0.0204195,0.001004803,0.2015783],"study_design_scores_gemma":[0.00006145593,0.0005047912,0.9239181,0.00005200444,0.0001692938,0.0009472537,0.001684851,0.02164983,0.02305023,0.02698017,0.0008614675,0.0001205384],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835545,0.0001431362,0.00844709,0.0001455112,0.00002063213,0.00001677021,0.00004839906,0.00006500921,0.007558914],"genre_scores_gemma":[0.9983091,0.00004583289,0.001248392,0.00002263328,0.000008752259,0.000008717971,0.00002838518,0.00004382055,0.0002841607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004083609,"threshold_uncertainty_score":0.01366103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009228659381102473,"score_gpt":0.2531996825512671,"score_spread":0.2439710231701646,"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."}}