{"id":"W2121975023","doi":"10.1111/j.1467-7687.2008.00685.x","title":"The effect of functional morphemes on word segmentation in preverbal infants","year":2008,"lang":"en","type":"article","venue":"Developmental Science","topic":"Language Development and Disorders","field":"Psychology","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Morpheme; Noun; Functor; Psychology; Linguistics; Mean length of utterance; Nonsense; Part of speech; Natural language processing; Artificial intelligence; Language development; Computer science; Mathematics; Developmental psychology; Chemistry; Pure 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005572826,0.0001016929,0.00009084761,0.0001223959,0.0003081837,0.00001442005,0.0002404983,0.00002846469,0.0004448126],"category_scores_gemma":[0.00008491873,0.00006616444,0.00002109884,0.0007132086,0.000427013,0.0001506838,0.00006040921,0.00007233871,0.0001664359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001233227,"about_ca_system_score_gemma":0.0001432731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006013575,"about_ca_topic_score_gemma":0.00004566507,"domain_scores_codex":[0.9987697,0.000050199,0.0002084647,0.0002434984,0.000452783,0.00027534],"domain_scores_gemma":[0.9996096,0.0001651167,0.00006543138,0.00009646182,0.00001986245,0.00004353422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004771925,0.00007875945,0.9054878,0.000005275167,0.00001837158,0.00002659768,0.008164876,0.00002092502,0.006574951,0.0004455645,0.002769886,0.07592974],"study_design_scores_gemma":[0.0008806972,0.00008085347,0.9820935,0.00001177812,0.000001191554,0.00001976085,0.0008603709,0.00000728446,0.01554748,0.00002934926,0.0003649129,0.0001027764],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764621,0.00005675537,0.00002352257,0.00004749798,0.0004888036,0.0002353059,0.000001224193,0.00001585033,0.02266899],"genre_scores_gemma":[0.9982044,0.0000081228,0.0003083915,0.00009035312,0.00001096082,0.00005596287,0.000006645935,0.000004370427,0.001310784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07660568,"threshold_uncertainty_score":0.4870386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385200610140448,"score_gpt":0.2782615883218462,"score_spread":0.2644095822204417,"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."}}