{"id":"W3161549544","doi":"10.31234/osf.io/e9n8w","title":"A Distributional and Sensorimotor Analysis of Noun and Verb Fluency","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Noun; Verb; Semantics (computer science); Psycholinguistics; Linguistics; Mental lexicon; Psychology; Verbal fluency test; Embodied cognition; Natural language processing; Cognitive psychology; Semantic similarity; Fluency; Cognition; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001085209,0.0001121843,0.000301545,0.0001633593,0.00004011744,0.00003483902,0.00004225318,0.0002201767,0.005618245],"category_scores_gemma":[0.00005522206,0.0001115862,0.00008116624,0.0003243842,0.00005984886,0.00003922763,0.0001067668,0.0001421031,0.000003999643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003551474,"about_ca_system_score_gemma":0.00004986265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002363557,"about_ca_topic_score_gemma":0.00005196144,"domain_scores_codex":[0.999086,0.00008142221,0.0002843098,0.0003364026,0.0001322406,0.00007966891],"domain_scores_gemma":[0.9992533,0.00006588618,0.0001621142,0.000235356,0.000233777,0.00004960793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005554365,0.0002933986,0.9420411,0.0001637595,0.005246016,0.00001027073,0.002154167,0.0002718316,0.0005839586,0.04164875,0.002337622,0.005193606],"study_design_scores_gemma":[0.0002183119,0.00001286288,0.99306,0.00001032667,0.000602266,0.000003245945,0.0004502397,0.004082606,0.00002955231,0.0001122186,0.001298183,0.0001202047],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505057,0.0003591792,0.04287697,0.0003732893,0.0003699521,0.0001252981,0.0002485443,0.00003079196,0.00511029],"genre_scores_gemma":[0.9958772,0.00009430813,0.0007183356,0.0001194596,0.00004424694,0.00001282964,0.001540467,0.00000618803,0.001586934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05101891,"threshold_uncertainty_score":0.9952908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02877898535335304,"score_gpt":0.3252220420934689,"score_spread":0.2964430567401158,"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."}}