{"id":"W4393037055","doi":"10.1167/jov.24.3.6","title":"Corrective mechanisms of motion extrapolation","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"West China Hospital, Sichuan University; Sichuan University; McGill University Health Centre; National Natural Science Foundation of China; McGill University","keywords":"Overshoot (microwave communication); Extrapolation; Position (finance); Motion perception; Motion (physics); Perception; Bar (unit); Computer science; Sensory system; Computer vision; Psychophysics; Artificial intelligence; Object (grammar); Transient (computer programming); Physics; Control theory (sociology); Mathematics; Psychology; Mathematical analysis; 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":[0.0005780193,0.0004428232,0.0002090221,0.0005272783,0.0002651653,0.000702638,0.0008555003,0.0007094493,0.003161861],"category_scores_gemma":[0.004661362,0.000238539,0.0003246267,0.000174307,0.0005420377,0.00133692,0.001036461,0.0007150137,0.0003536725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003281448,"about_ca_system_score_gemma":0.0003105803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003968944,"about_ca_topic_score_gemma":0.0001678831,"domain_scores_codex":[0.9997028,0.000045694,0.00001543808,0.00007209342,0.0001106536,0.0000532671],"domain_scores_gemma":[0.9986389,0.0004975748,0.0002682817,0.000237631,0.0002426969,0.0001147781],"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":[0.0006564721,0.0001472547,0.005069167,0.0004315975,0.00006772264,0.001079791,0.001052202,0.01578191,0.724651,0.1002184,0.001103724,0.1497409],"study_design_scores_gemma":[0.0003531522,0.001867056,0.0781325,0.0002816728,0.0001555304,0.003198685,0.0008079796,0.3537514,0.258958,0.288379,0.0138376,0.0002774056],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.719188,0.003025788,0.2500419,0.001259973,0.0004326694,0.0001401673,0.0001328171,0.0017028,0.02407586],"genre_scores_gemma":[0.9902294,0.0003753205,0.00778635,0.0000663677,0.00004227049,0.00002872342,0.00003406508,0.0000326396,0.001404757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003161861,"threshold_uncertainty_score":0.01057744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04755171519462105,"score_gpt":0.3625719381414184,"score_spread":0.3150202229467973,"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."}}