{"id":"W2146203184","doi":"10.1109/cvpr.1992.223269","title":"Performance of optical flow techniques","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":740,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Western University","funders":"","keywords":"Smoothness; Optical flow; Computer science; Flow (mathematics); Measure (data warehouse); Computation; Algorithm; Differential (mechanical device); Artificial intelligence; Mathematics; Image (mathematics); Data mining; Mathematical analysis; Geometry; Physics","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":[0.00009092544,0.00003696851,0.00005414122,0.00003100482,0.00002157145,0.00001095844,0.000189066,0.00001139862,0.00003416839],"category_scores_gemma":[0.00002393741,0.00002843104,0.00001640861,0.0001245095,0.00002188044,0.0002863756,0.00004293751,0.00003675415,0.00001653073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004845498,"about_ca_system_score_gemma":0.0000138929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.43977e-7,"about_ca_topic_score_gemma":4.413918e-8,"domain_scores_codex":[0.999634,0.000007542729,0.00008538835,0.00009700253,0.00008691262,0.00008920363],"domain_scores_gemma":[0.9997071,0.00001523162,0.00001493439,0.0002015776,0.00003277491,0.00002836526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[8.766929e-7,0.00002711564,0.0006697911,0.00000613606,0.000001100587,9.647092e-7,0.00003578287,0.00001904546,0.007326688,0.1487766,0.0003233784,0.8428125],"study_design_scores_gemma":[0.00005812051,0.00006031748,0.0002956752,0.00001169926,4.331648e-7,0.00001108873,0.000005399599,0.2438183,0.7428038,0.0009337894,0.01193205,0.00006925805],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003190525,0.00001180727,0.8823885,0.00008690031,0.00003826114,0.00002574106,3.082883e-8,0.00009429172,0.1141639],"genre_scores_gemma":[0.3705509,0.00000882385,0.6290265,0.0001264274,0.000002512543,9.341148e-7,2.817898e-8,0.000001197079,0.0002826662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8427433,"threshold_uncertainty_score":0.1159384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01110070795610745,"score_gpt":0.268638941338608,"score_spread":0.2575382333825005,"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."}}