{"id":"W3010834168","doi":"10.1037/xlm0000820","title":"Proactive control in the Stroop task: A conflict-frequency manipulation free of item-specific, contingency-learning, and color-word correlation confounds.","year":2020,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stroop effect; Psychology; Color term; Cognitive psychology; Task (project management); Word lists by frequency; Contingency; Cognition; Linguistics; Artificial intelligence; Computer science; Neuroscience; Sentence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003742145,0.0001612865,0.0003159535,0.0001020019,0.0002043022,0.00002908487,0.0001351483,0.0001104709,0.000047229],"category_scores_gemma":[0.0003192208,0.0001236856,0.00005967846,0.000161806,0.0004064536,0.0002788561,0.00002954242,0.0007316818,0.000003095592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001295588,"about_ca_system_score_gemma":0.000008772951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002979673,"about_ca_topic_score_gemma":9.667796e-7,"domain_scores_codex":[0.9981263,0.0006985785,0.0005156365,0.0002867757,0.0002088191,0.0001639505],"domain_scores_gemma":[0.9987803,0.0003449133,0.0006654951,0.00006254197,0.00008927363,0.00005747559],"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":[0.001446136,0.0002224069,0.01784067,0.000008286222,0.00002190491,0.00006197029,0.005164857,0.00001363534,0.9725425,0.0001814711,0.000154065,0.002342069],"study_design_scores_gemma":[0.04660538,0.0277825,0.4855668,0.0003974663,0.0005467154,0.003311311,0.05737128,0.001401008,0.3677551,0.002550835,0.005391017,0.001320558],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942764,0.001191664,0.0001754063,0.001488308,0.0002200823,0.000362046,0.000003762561,0.00001390089,0.002268453],"genre_scores_gemma":[0.9983078,0.0002886552,0.00004128847,0.001211377,0.00009897625,0.00001466455,0.000003103827,0.000009847671,0.00002435046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6047874,"threshold_uncertainty_score":0.504375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175872266585677,"score_gpt":0.3684712580344513,"score_spread":0.2508840313758837,"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."}}