{"id":"W1973102016","doi":"10.3758/pbr.15.4.866","title":"On finding negative priming from distractors","year":2008,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Negative priming; Psychology; Phenomenon; Priming (agriculture); Cognitive psychology; Set (abstract data type); Mechanism (biology); Inhibition of return; Variety (cybernetics); Control (management); Selective attention; Social psychology; Cognition; Visual attention; Neuroscience; Epistemology; Artificial intelligence; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001007431,0.0002627496,0.0004309884,0.00003642913,0.0003117264,0.00001430807,0.0003379227,0.00005241372,0.001835802],"category_scores_gemma":[0.0002831972,0.0002046525,0.0001726648,0.000133695,0.0002263042,0.0000438973,0.00005505847,0.0003285583,0.003920245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004307568,"about_ca_system_score_gemma":0.000009104411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003303337,"about_ca_topic_score_gemma":0.000001243252,"domain_scores_codex":[0.9982685,0.0001498025,0.0003981318,0.000722893,0.0001494583,0.00031124],"domain_scores_gemma":[0.9988053,0.0005048584,0.0002168525,0.000369092,0.00001261705,0.00009128183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002452116,0.001082273,0.006052342,0.0004041939,0.00004957425,0.0003756705,0.0006473554,0.000002755572,0.0740938,0.0004824103,0.8160682,0.1004962],"study_design_scores_gemma":[0.001323028,0.0003601761,0.03667296,0.003885935,0.0001342763,0.0001451433,0.00003663129,0.00000137976,0.03474947,0.001069991,0.9205037,0.001117318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750333,0.005375973,0.00000626451,0.009668472,0.00113117,0.0005148956,0.00003784861,0.0001078682,0.008124204],"genre_scores_gemma":[0.9367107,0.04538122,0.0001869864,0.01623114,0.0001685468,0.0000761696,0.000004559161,0.00003022173,0.001210439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1044355,"threshold_uncertainty_score":0.9990767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2444749778009437,"score_gpt":0.3870046129437151,"score_spread":0.1425296351427714,"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."}}