{"id":"W2597238469","doi":"10.1037/xlm0000390","title":"Distinguishing discrete and gradient category structure in language: Insights from verb-particle constructions.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Verb; Representation (politics); Cline (biology); Computer science; Natural language processing; Consistency (knowledge bases); Linguistics; Component (thermodynamics); Mental representation; Psychology; Class (philosophy); Cognitive psychology; Artificial intelligence; Cognition","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008561604,0.0001678088,0.0001713082,0.0009262564,0.0001927772,0.001485054,0.0005224372,0.0003961367,0.001966037],"category_scores_gemma":[0.01060328,0.0001462719,0.0001880205,0.000781343,0.001574691,0.002567151,0.0009833955,0.0008909701,0.0002325506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004390315,"about_ca_system_score_gemma":0.0003361393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001645244,"about_ca_topic_score_gemma":0.003442277,"domain_scores_codex":[0.9997111,0.00009930821,0.00001946053,0.00008057431,0.00007071011,0.00001894813],"domain_scores_gemma":[0.9957327,0.002660307,0.0007356801,0.0005802548,0.0001728975,0.0001180294],"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":[0.001142987,0.0003434012,0.1449327,0.0006687726,0.00009615746,0.001477035,0.02931611,0.004989623,0.1324198,0.1200351,0.001508004,0.5630704],"study_design_scores_gemma":[0.00004426442,0.0005416957,0.6012079,0.0001936829,0.0001073398,0.003758649,0.01301571,0.04870017,0.04262745,0.2798631,0.009852297,0.00008785754],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9432209,0.0003779329,0.04563587,0.0005335737,0.00001360034,0.00003139648,0.0001999367,0.0001258241,0.009860944],"genre_scores_gemma":[0.9856352,0.0001547403,0.01307562,0.00004030182,0.000004132621,0.00001961743,0.0001087733,0.00003521368,0.0009263468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001966037,"threshold_uncertainty_score":0.006577015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02515799533211804,"score_gpt":0.3365469933070269,"score_spread":0.3113889979749089,"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."}}