{"id":"W3089329285","doi":"10.1177/2041669520939107","title":"Jumpy and Jerky: When Peripheral Vision Faces Reverse-Phi","year":2020,"lang":"en","type":"article","venue":"i-Perception","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Centre National de la Recherche Scientifique; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Peripheral vision; Foveal; Illusion; Flicker; Motion (physics); Peripheral; Stimulus (psychology); Eccentricity (behavior); Annulus (botany); Motion perception; Jump; Computer vision; Artificial intelligence; Psychology; Communication; Computer science; Physics; Neuroscience; Cognitive psychology; Chemistry; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001193324,0.000164092,0.0001523211,0.00004886613,0.0002749019,0.0001871194,0.0001428267,0.0001079531,0.002681545],"category_scores_gemma":[0.0001262206,0.0001498986,0.00004836455,0.0001588962,0.0000990831,0.0005070265,0.00006245622,0.0001860615,0.0006762462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003952913,"about_ca_system_score_gemma":0.0000175048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001571232,"about_ca_topic_score_gemma":0.000003635753,"domain_scores_codex":[0.9986705,0.0001309741,0.000183933,0.0005122253,0.0002915249,0.0002108268],"domain_scores_gemma":[0.9995868,0.00002249645,0.00006178927,0.0001240776,0.00002717363,0.0001777117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005424937,0.00002451924,0.00008669674,0.00003315355,8.679887e-7,0.000003552913,0.006001767,0.000009812403,0.9508889,0.0001358147,0.004471763,0.03828895],"study_design_scores_gemma":[0.009131885,0.007600752,0.07356665,0.0006478276,0.000196212,0.0003412415,0.0250319,0.1965929,0.1761064,0.01774569,0.4882801,0.004758521],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816831,0.00001907463,0.006436276,0.008303376,0.0002955327,0.0002091397,0.00001151454,0.0003414055,0.002700554],"genre_scores_gemma":[0.9857554,0.0001066318,0.001498617,0.01122302,0.0002270864,0.000008212724,0.000007349923,0.00002423532,0.001149388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7747825,"threshold_uncertainty_score":0.9982302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07027278564264527,"score_gpt":0.3247912309476383,"score_spread":0.254518445304993,"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."}}