{"id":"W2115091443","doi":"10.1016/j.cognition.2014.01.001","title":"Get rich quick: The signal to respond procedure reveals the time course of semantic richness effects during visual word recognition","year":2014,"lang":"en","type":"article","venue":"Cognition","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Categorization; Psychology; Lexical decision task; Semantics (computer science); Semantic memory; Cognitive psychology; Task (project management); Object (grammar); Word recognition; Word (group theory); Cognition; Natural language processing; Linguistics; Artificial intelligence; Computer science; Reading (process)","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":[0.0006367691,0.0003878547,0.0005026991,0.0004689108,0.0002542189,0.0005695419,0.0004671327,0.0005270625,0.007639407],"category_scores_gemma":[0.003426613,0.0004051773,0.0002327008,0.0003711439,0.00079803,0.001100977,0.0006696226,0.001406254,0.001199304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001465749,"about_ca_system_score_gemma":0.000278258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004881241,"about_ca_topic_score_gemma":0.001955262,"domain_scores_codex":[0.9997484,0.00003639127,0.00001438712,0.00007224875,0.00006898417,0.00005957558],"domain_scores_gemma":[0.9982993,0.0009767148,0.0002298782,0.000200779,0.00006805198,0.0002252413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002069604,0.0001250313,0.001028687,0.0001155544,0.00002699761,0.0001030938,0.0001267584,0.0001416943,0.974335,0.0009301961,0.0006927671,0.02030479],"study_design_scores_gemma":[0.0004640785,0.002795951,0.189891,0.0000469422,0.0001702804,0.001647319,0.0003129055,0.0112619,0.7828534,0.007020119,0.003386661,0.0001493728],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622266,0.0003412847,0.03112474,0.0003065722,0.0001788749,0.00006777537,0.0009177878,0.0007347051,0.00410167],"genre_scores_gemma":[0.9674183,0.0003469013,0.02441005,0.0003825801,0.000112508,0.0002163842,0.0008480821,0.001312207,0.004952968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007639407,"threshold_uncertainty_score":0.02555639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343416416409183,"score_gpt":0.2763276768608405,"score_spread":0.2628935126967487,"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."}}