{"id":"W2579005319","doi":"","title":"Generalizing between form and meaning using learned verb classes","year":2011,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Language Development and Disorders","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Verb; Computer science; Meaning (existential); Generalization; Linguistics; Reflexive verb; Artificial intelligence; Language acquisition; Natural language processing; Representation (politics); Psychology; Cognitive science; Modal verb; Philosophy; Epistemology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001512069,0.0003078618,0.0002894025,0.0002010937,0.0002007247,0.0005669931,0.0003063977,0.0002023184,0.002003874],"category_scores_gemma":[0.00008035886,0.0002844693,0.00009828453,0.0003143055,0.0001021647,0.002751339,0.0002564931,0.0003307835,0.0008826709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002154201,"about_ca_system_score_gemma":0.00005322012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002814504,"about_ca_topic_score_gemma":0.000002488638,"domain_scores_codex":[0.9982458,0.00006919957,0.0003934048,0.0004999177,0.0002077247,0.0005840032],"domain_scores_gemma":[0.9992042,0.0000885287,0.0001315026,0.000289368,0.00002004707,0.0002663993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001035605,0.00007812402,0.9614985,0.00003041337,0.000147544,0.00008528331,0.001718983,1.861334e-7,0.00009476378,0.01038742,0.0007521785,0.02510304],"study_design_scores_gemma":[0.007914118,0.0005854391,0.4608093,0.0004468967,0.000396198,0.0002072472,0.006805791,0.0001079442,0.007582988,0.2000929,0.3100451,0.00500613],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8187295,0.0004130141,0.000303486,0.00006841328,0.0001534053,0.0001668757,0.0001938861,0.0003113764,0.17966],"genre_scores_gemma":[0.9938065,0.000008594134,0.003890279,0.0004785802,0.000162764,0.00001015988,0.0002737063,0.00009809456,0.001271352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5006892,"threshold_uncertainty_score":0.9999607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06766723877055496,"score_gpt":0.2715825069451036,"score_spread":0.2039152681745486,"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."}}