{"id":"W2140001076","doi":"10.3389/fpsyg.2011.00253","title":"Motor Response Selection in Overt Sentence Production: A Functional MRI Study","year":2011,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Deafness and Other Communication Disorders; Canadian Institutes of Health Research; Pritzker School of Medicine; University of Chicago","keywords":"Sentence; Psychology; Selection (genetic algorithm); Inferior frontal gyrus; Task (project management); Premotor cortex; Supplementary motor area; Context (archaeology); Gesture; Cognitive psychology; Functional magnetic resonance imaging; Neuroscience; Set (abstract data type); Artificial intelligence; Computer science; Medicine; Dorsum","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":[0.0006255984,0.0001414482,0.0001951882,0.0004802175,0.00006415424,0.000005988372,0.0002095941,0.0001184361,0.0001206441],"category_scores_gemma":[0.0005423544,0.0001347075,0.00003735647,0.0006147746,0.0001848278,0.0001352495,0.00003613115,0.0003630155,0.00003294988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005045826,"about_ca_system_score_gemma":0.00003629446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003360836,"about_ca_topic_score_gemma":0.00006692546,"domain_scores_codex":[0.997599,0.0008855108,0.0002894132,0.000799054,0.0001142998,0.0003126957],"domain_scores_gemma":[0.9995652,0.00005881597,0.0000770308,0.0002385956,0.00002245235,0.0000378414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01251462,0.002581699,0.5648195,0.000006028662,0.00001266688,0.00174993,0.006245123,0.000008501386,0.3879389,0.00001884343,0.02043138,0.003672807],"study_design_scores_gemma":[0.003284665,0.002426503,0.9586644,0.00002003453,0.00001398675,0.001970169,0.002405035,0.0000926823,0.02270099,0.003645163,0.004320091,0.0004562965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992232,0.00005697348,0.0008184142,0.0005423473,0.005108086,0.0005020075,0.000002233435,0.00006428864,0.0006736354],"genre_scores_gemma":[0.9958366,0.00002833875,0.001430955,0.001702528,0.0001382517,0.00007681691,7.007945e-7,0.00001382611,0.0007720499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3938449,"threshold_uncertainty_score":0.5493211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05502404163359709,"score_gpt":0.3144495098272669,"score_spread":0.2594254681936698,"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."}}