{"id":"W2512194521","doi":"10.1016/j.cognition.2016.07.010","title":"It’s all in the delivery: Effects of context valence, arousal, and concreteness on visual word processing","year":2016,"lang":"en","type":"article","venue":"Cognition","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Concreteness; Psychology; Valence (chemistry); Lexical decision task; Cognitive psychology; Embodied cognition; Semantics (computer science); Word recognition; Word (group theory); Cognition; Word processing; Age of Acquisition; Semantic memory; Linguistics; Natural language processing; Artificial intelligence; Computer science","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":[0.0004009865,0.0001983952,0.0002085172,0.0001237802,0.0001549559,0.0008294015,0.00009358299,0.0001269616,0.00165466],"category_scores_gemma":[0.003953665,0.0001421719,0.00009839911,0.0001028995,0.0003232019,0.000369766,0.0004363533,0.0003475734,0.0001619332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001261873,"about_ca_system_score_gemma":0.0001248532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002416181,"about_ca_topic_score_gemma":0.0005781427,"domain_scores_codex":[0.9997488,0.00009795911,0.00001988864,0.00006166477,0.00004648305,0.00002522727],"domain_scores_gemma":[0.9985555,0.0008705555,0.0002534283,0.00008627136,0.00009227917,0.00014201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.007926396,0.000397123,0.04560649,0.0003477632,0.0001186903,0.0003692383,0.002585625,0.0003596561,0.8918465,0.0008637874,0.0002916055,0.04928725],"study_design_scores_gemma":[0.0001510128,0.004523618,0.8697163,0.0001089995,0.0002799001,0.001534537,0.002023218,0.002762155,0.1125608,0.004041296,0.002237306,0.00006094896],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980024,0.0001196622,0.0005183705,0.00002687475,0.000009737614,0.00000606321,0.0000281222,0.00001017874,0.001278664],"genre_scores_gemma":[0.9984485,0.0001022654,0.0009979871,0.00003821038,0.000009330551,0.0000126729,0.00004882811,0.0000238992,0.0003183956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00165466,"threshold_uncertainty_score":0.005535364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03925958361175824,"score_gpt":0.3098516292403593,"score_spread":0.2705920456286011,"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."}}