{"id":"W2135110205","doi":"10.1016/s0093-934x(02)00521-7","title":"Semantics and semantic errors: Implicit access to semantic information from words and nonwords in deep dyslexia","year":2003,"lang":"en","type":"article","venue":"Brain and Language","topic":"Reading and Literacy Development","field":"Psychology","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; University of Alberta; Chrysler (Canada)","funders":"","keywords":"Psychology; Semantics (computer science); Semantic memory; Cognitive psychology; Dyslexia; Reading (process); Natural language processing; Lexical access; Aphasia; Language disorder; Linguistics; Cognition; Computer science","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":[0.0003346268,0.0001750722,0.0002330585,0.000242524,0.00006571627,0.0002084011,0.00009279972,0.0001041126,0.0001631322],"category_scores_gemma":[0.0001240595,0.0001591453,0.00001569017,0.0002337528,0.00003685767,0.0002957323,0.00007229304,0.0001374492,0.00003158273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001712313,"about_ca_system_score_gemma":0.00001316152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000957144,"about_ca_topic_score_gemma":0.0004750926,"domain_scores_codex":[0.9989461,0.00009748787,0.000296533,0.0002630632,0.0001066117,0.0002902436],"domain_scores_gemma":[0.9994045,0.0001769851,0.00006387894,0.0002045081,0.00001463543,0.0001355236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001559467,0.0001381979,0.2988227,0.0002882737,0.0001411566,0.0002112654,0.4420452,0.000008782392,0.001082562,0.007033957,0.00447042,0.2456016],"study_design_scores_gemma":[0.002308167,0.0001016812,0.9489307,0.0002900639,0.00003369558,0.0001318653,0.01980275,0.0004728257,0.000230693,0.001026232,0.02605608,0.0006152879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915004,0.0009037127,0.001555386,0.0008824226,0.0001738855,0.0002943248,0.00001216352,0.00003783009,0.004639915],"genre_scores_gemma":[0.9958184,0.0000335658,0.0009400135,0.002612376,0.00003375992,0.00002481845,0.00003055561,0.00001449735,0.0004920602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.650108,"threshold_uncertainty_score":0.6489756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079616278159722,"score_gpt":0.3053262610630998,"score_spread":0.2945300982815026,"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."}}