{"id":"W2625943057","doi":"10.1044/2017_jslhr-s-16-0298","title":"Using Network Science Measures to Predict the Lexical Decision Performance of Adults Who Stutter","year":2017,"lang":"en","type":"article","venue":"Journal of Speech Language and Hearing Research","topic":"Stuttering Research and Treatment","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Psycholinguistics; Psychology; Lexical decision task; Stuttering; Centrality; Cognitive psychology; Closeness; Mental lexicon; Linguistics; Artificial intelligence; Developmental psychology; Computer science; Cognition; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005463284,0.00008493837,0.0002113709,0.0002678497,0.0009974379,0.0002414999,0.0007582737,0.00004739123,0.00007395183],"category_scores_gemma":[0.0007172243,0.00004958281,0.00005265637,0.0002321393,0.0005925925,0.0001598763,0.0004797417,0.0005548116,0.00001182426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007523848,"about_ca_system_score_gemma":0.0001500771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006734438,"about_ca_topic_score_gemma":0.00004136857,"domain_scores_codex":[0.9975039,0.00009873464,0.0002793611,0.0001950716,0.001344493,0.0005784428],"domain_scores_gemma":[0.9983175,0.0002981373,0.0001192985,0.0005424641,0.0004852666,0.0002373628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002489288,0.0001291593,0.4659649,0.00004718883,0.0001017512,0.0005352467,0.007693565,0.00008206853,0.007812538,0.0001105657,0.00115641,0.5138774],"study_design_scores_gemma":[0.0008973444,0.001230673,0.9897461,0.0008159481,0.0000108165,0.0002747286,0.001449311,0.0002773035,0.004836958,0.00009084418,0.0003033108,0.00006669152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965912,0.0009652026,0.00005975202,0.0005475912,0.0001752207,0.00019577,0.000001514565,0.00000283629,0.001460925],"genre_scores_gemma":[0.9973633,0.0001027793,0.001666638,0.00002653144,0.0006106247,0.000003042739,5.734778e-8,0.000009519637,0.0002175275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5237812,"threshold_uncertainty_score":0.7671586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1654726612087362,"score_gpt":0.4861872887285666,"score_spread":0.3207146275198304,"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."}}