{"id":"W4392144222","doi":"10.1111/cogs.13413","title":"Determining the Relativity of Word Meanings Through the Construction of Individualized Models of Semantic Memory","year":2024,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Topic Modeling","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Word (group theory); Computer science; Natural language processing; Semantics (computer science); Linguistics; Cognitive science; Artificial intelligence; Psychology; Philosophy; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004182008,0.0004768619,0.0006872362,0.004167111,0.0009368351,0.004437878,0.001166685,0.0006899955,0.001596217],"category_scores_gemma":[0.02842449,0.0007085614,0.00126747,0.002740277,0.002790291,0.009137196,0.002859813,0.001385229,0.000316727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317538,"about_ca_system_score_gemma":0.0008345621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002637555,"about_ca_topic_score_gemma":0.003683054,"domain_scores_codex":[0.9974348,0.001278865,0.0002065836,0.0006689148,0.0003070759,0.0001038278],"domain_scores_gemma":[0.9888524,0.007743705,0.0009729688,0.001795098,0.0005083444,0.0001274824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005194304,0.0002791209,0.1265455,0.0006268737,0.0007162705,0.0004384384,0.03621333,0.06223205,0.01566886,0.3486736,0.001844098,0.4062425],"study_design_scores_gemma":[0.00004320182,0.0001939509,0.05667287,0.0001544323,0.0002353554,0.0006180009,0.01049888,0.3840786,0.007328399,0.5317637,0.008242201,0.000170432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5372071,0.0003383829,0.4546992,0.0002599965,0.00002278242,0.0001074021,0.0003003164,0.0003606453,0.006704318],"genre_scores_gemma":[0.9080551,0.0001725259,0.09078115,0.00002150373,0.0000132104,0.0001578627,0.0003285097,0.00008239739,0.000387628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004437878,"threshold_uncertainty_score":0.02211684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05578627591767514,"score_gpt":0.3020556721302243,"score_spread":0.2462693962125492,"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."}}