{"id":"W1529948953","doi":"10.1002/9781444301007.ch14","title":"Normal and Pathological Semantic Processing of Words","year":2008,"lang":"en","type":"other","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Semantic memory; Natural language processing; Computer science; Psychology; Artificial intelligence; Pathological; Neuroscience; Pathology; Cognition; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.00009165908,0.0000972904,0.0001607791,0.0001403406,0.00003613779,0.00003299314,0.0002974707,0.00007779532,0.00009053908],"category_scores_gemma":[0.00001721135,0.00007088585,0.00002442642,0.0002227828,0.0001508434,0.0001111995,0.0002438727,0.00007148342,0.0000124743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000272911,"about_ca_system_score_gemma":0.00005104421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002063918,"about_ca_topic_score_gemma":0.00001170547,"domain_scores_codex":[0.9992967,0.00001544625,0.00009847413,0.000276679,0.0001630206,0.0001497245],"domain_scores_gemma":[0.9997042,0.00001388411,0.00008178093,0.0001357069,0.00002523061,0.00003924471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001988258,0.00009130563,0.001838169,0.0002764985,0.00001333429,0.0001927243,0.001333164,4.120418e-7,0.0004975568,0.006124219,0.06034833,0.9292823],"study_design_scores_gemma":[0.002633697,0.001140798,0.04123124,0.005318201,0.00009358266,0.002343364,0.0008991588,0.03965456,0.002511462,0.006036368,0.8935772,0.004560369],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001942851,0.0004971582,0.3160957,0.00006634375,0.0000642891,0.0000709697,6.409861e-7,0.0001136411,0.682897],"genre_scores_gemma":[0.1499887,0.0007310492,0.09481476,0.0006489434,0.0001862554,0.00001000901,0.000001822454,0.0000675179,0.7535509],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.924722,"threshold_uncertainty_score":0.2890641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173610751847047,"score_gpt":0.2494727594108382,"score_spread":0.2277366518923677,"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."}}