{"id":"W3101824727","doi":"10.1111/cdev.13469","title":"The Development of Attention to Objects and Scenes: From Object-Biased to Unbiased","year":2020,"lang":"en","type":"article","venue":"Child Development","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Psychology; Selective attention; Cognitive psychology; Stimulus (psychology); Visual attention; Rapid serial visual presentation; Object (grammar); Visual search; Developmental psychology; Cognition; Artificial intelligence; Computer science; Neuroscience","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":[0.001226239,0.0002174013,0.0002411995,0.0005122642,0.0001718453,0.0005586002,0.0002229888,0.0002508505,0.0008204933],"category_scores_gemma":[0.00446768,0.0002647379,0.0002153416,0.0002088116,0.0007706496,0.000690576,0.0005923462,0.0005041574,0.0001205412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004624543,"about_ca_system_score_gemma":0.0005237579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004471542,"about_ca_topic_score_gemma":0.005853619,"domain_scores_codex":[0.9995871,0.000067229,0.00002833222,0.0001085345,0.0001478693,0.0000608371],"domain_scores_gemma":[0.9979047,0.0008209138,0.0006829156,0.0001487807,0.0002898157,0.0001528715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005339299,0.0002326736,0.6529397,0.000209789,0.00008355223,0.001001407,0.008876303,0.00086077,0.2041971,0.005058226,0.0005585229,0.125448],"study_design_scores_gemma":[0.00000955095,0.0003356257,0.9839019,0.00002958652,0.00002950329,0.0008188093,0.0006662102,0.0009451895,0.01052292,0.001678178,0.001046595,0.00001588168],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970035,0.0003073779,0.001367082,0.00004137541,0.000003949227,0.00001031586,0.00005145709,0.00001049007,0.001204532],"genre_scores_gemma":[0.9979546,0.0002594752,0.00134185,0.00002835552,0.000003020579,0.0000145381,0.00005801874,0.000006417078,0.000333707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004471542,"threshold_uncertainty_score":0.008891046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1237723656478384,"score_gpt":0.3293435563331198,"score_spread":0.2055711906852814,"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."}}