{"id":"W2119357094","doi":"10.3758/bf03192877","title":"Dynamic object recognition in pigeons and humans","year":2006,"lang":"en","type":"article","venue":"Learning & Behavior","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Max-Planck-Gesellschaft","keywords":"Object (grammar); Motion (physics); Psychology; Biological motion; Artificial intelligence; Communication; Task (project management); Cognitive neuroscience of visual object recognition; Computer vision; Pattern recognition (psychology); Cognitive psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001944203,0.0001285926,0.0001463326,0.0001514407,0.0001347075,0.00003594574,0.00005584621,0.00008379183,0.000835814],"category_scores_gemma":[0.00002007721,0.0001363061,0.00003617278,0.00013966,0.00004415819,0.00004475078,0.00002746337,0.0004427882,0.0003752427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000479056,"about_ca_system_score_gemma":0.00001125874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006835471,"about_ca_topic_score_gemma":0.0004926088,"domain_scores_codex":[0.9989768,0.00010914,0.0002051928,0.0003373073,0.00009420612,0.0002773855],"domain_scores_gemma":[0.9997451,0.00004468792,0.00006531311,0.00009555886,0.0000148543,0.0000345322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002660614,0.0002363252,0.9145706,0.000004939892,0.000005500023,0.0001385701,0.001662518,0.00001976729,0.005735826,0.0002743192,0.000108957,0.07721602],"study_design_scores_gemma":[0.0005185654,0.00008321121,0.9948058,0.00003933173,0.00002033908,0.00002384261,0.0003880603,0.00001182559,0.00001919105,0.00004007693,0.003866679,0.0001830543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902191,0.000178396,0.00002326213,0.00008655216,0.0001619297,0.0001543133,0.000002675338,0.0001250949,0.009048666],"genre_scores_gemma":[0.9929472,0.000007853737,0.0004154999,0.000036958,0.00003917667,0.00006169958,0.00007875021,0.00002586845,0.006387058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08023517,"threshold_uncertainty_score":0.9151578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416410238673006,"score_gpt":0.2844375652344948,"score_spread":0.2702734628477648,"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."}}