{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005468365,0.0003058906,0.0003039716,0.0005534305,0.0003092914,0.0008040043,0.0003786442,0.0007917722,0.002195366],"category_scores_gemma":[0.001752174,0.0003077325,0.0002166426,0.0001033973,0.001463245,0.0008591895,0.000436863,0.0005755858,0.0002967635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006124586,"about_ca_system_score_gemma":0.0003760988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01199083,"about_ca_topic_score_gemma":0.01010959,"domain_scores_codex":[0.9997799,0.00003459274,0.000008975408,0.00009152228,0.00004069775,0.0000443779],"domain_scores_gemma":[0.9990859,0.0002855414,0.0001539561,0.0001452932,0.00009848597,0.00023079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004625863,0.001612192,0.4256903,0.0002106077,0.0002280422,0.004432248,0.01332281,0.004619907,0.377687,0.01437067,0.003398825,0.1498014],"study_design_scores_gemma":[0.0001004685,0.002131835,0.957769,0.00003906776,0.0000622404,0.004286386,0.002731668,0.007990432,0.01703749,0.004246115,0.003516065,0.00008929022],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979514,0.0001559781,0.0003668837,0.00007218467,0.00001322981,0.000004909418,0.00002978308,0.00001733696,0.001388356],"genre_scores_gemma":[0.9977012,0.0000682174,0.0004976028,0.00004849384,0.000003530016,0.000005984591,0.00006018167,0.00001262413,0.001602077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01199083,"threshold_uncertainty_score":0.0238421,"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."}}