{"id":"W2284194785","doi":"10.1371/journal.pone.0149413","title":"Visual Acceleration Perception for Simple and Complex Motion Patterns","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Acceleration; Motion (physics); Motion perception; Perception; Computer vision; Physics; Artificial intelligence; Sign (mathematics); Visual perception; Computer science; Communication; Mathematics; Psychology; Classical mechanics; Mathematical analysis; Neuroscience","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":[],"consensus_categories":[],"category_scores_codex":[0.00009376952,0.00008113597,0.00009440363,0.00005017897,0.0001879846,0.0000738598,0.00005191558,0.00004863548,0.0006825052],"category_scores_gemma":[0.0001443331,0.00006182669,0.00001946218,0.0000474305,0.00002825403,0.0002942068,0.00002128361,0.00003125437,0.00007811475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002801611,"about_ca_system_score_gemma":0.00000630558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002704949,"about_ca_topic_score_gemma":0.000004969738,"domain_scores_codex":[0.9992461,0.00004779801,0.0001235096,0.0002606187,0.0001797481,0.0001422238],"domain_scores_gemma":[0.9997112,0.0000656605,0.00004959244,0.00007101306,0.0000473594,0.00005518458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002668623,0.0002361722,0.0005643547,0.0000448495,0.0000017286,1.120204e-7,0.0001458445,1.387801e-7,0.9675016,0.0002294937,0.00004834904,0.03120061],"study_design_scores_gemma":[0.001303846,0.00060461,0.03542265,0.0001032379,0.00003343479,0.000003141893,0.0001096642,0.01497763,0.9433128,0.003703181,0.0001712004,0.000254588],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9058597,7.122614e-7,0.09298349,0.0006792743,0.00003150043,0.0002535096,0.00002575864,0.00009647885,0.00006955536],"genre_scores_gemma":[0.997832,0.00003128727,0.000725456,0.0007856396,0.0001413128,0.00004288628,0.00001879969,0.00001506654,0.00040755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09225803,"threshold_uncertainty_score":0.7472953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2360825739198218,"score_gpt":0.3463700176153885,"score_spread":0.1102874436955667,"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."}}