{"id":"W3203536237","doi":"10.1080/13506285.2021.1918811","title":"Dividing attentional capture","year":2021,"lang":"en","type":"article","venue":"Visual Cognition","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Luck; Milestone; Psychology; Cognitive psychology; Cognitive science; Cognition; Visual attention; Epistemology; Neuroscience; Philosophy; History","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":[0.004749879,0.0007727455,0.000992912,0.001747444,0.001094665,0.00521792,0.002316074,0.002180379,0.006401352],"category_scores_gemma":[0.009078386,0.000486547,0.0007535173,0.0009755926,0.0084559,0.01144998,0.004012494,0.002705078,0.001266748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003023937,"about_ca_system_score_gemma":0.001545719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002189125,"about_ca_topic_score_gemma":0.001221879,"domain_scores_codex":[0.9960871,0.0006049907,0.0002294263,0.001360474,0.001329251,0.000388864],"domain_scores_gemma":[0.9949642,0.00242279,0.0006066334,0.0008499903,0.000864169,0.0002921206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000530905,0.00008106424,0.00497423,0.002318343,0.0002875022,0.0001994294,0.005856017,0.000704883,0.01500267,0.518371,0.008977702,0.4426963],"study_design_scores_gemma":[0.00009398617,0.0003272367,0.02690475,0.00174637,0.000263113,0.001318924,0.001996474,0.002590961,0.007999703,0.7944361,0.1621686,0.0001538153],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1152747,0.5129552,0.162252,0.02979038,0.006373846,0.0002658828,0.0006015778,0.0008913254,0.171595],"genre_scores_gemma":[0.8839779,0.07915509,0.01192422,0.00933567,0.004090983,0.0003689678,0.0002878983,0.0003158475,0.01054346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006401352,"threshold_uncertainty_score":0.02512008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2203322815785929,"score_gpt":0.4241643802434215,"score_spread":0.2038320986648285,"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."}}