{"id":"W2119303354","doi":"10.1109/ccece.1996.548138","title":"Optical flow based model for scene cut detection","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Block (permutation group theory); Frame (networking); Computer science; Computer vision; Artificial intelligence; Optical flow; Sequence (biology); Segmentation; Subsequence; Block size; Block-matching algorithm; Algorithm; Mathematics; Image (mathematics); Video tracking; Video processing; Telecommunications","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":[0.00005461606,0.00005580002,0.00005443967,0.00004164708,0.00008160091,0.00005442906,0.0001797216,0.00001905722,0.00003264755],"category_scores_gemma":[0.00003247764,0.00004736234,0.00003976016,0.00009925343,0.00001096658,0.0003243576,0.00003519674,0.00004107446,0.00004735378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001729066,"about_ca_system_score_gemma":0.00000591238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.086301e-7,"about_ca_topic_score_gemma":0.000002916914,"domain_scores_codex":[0.9994729,0.000004801954,0.00008264482,0.0001921086,0.0000953915,0.0001521117],"domain_scores_gemma":[0.9996423,0.00003629191,0.00001269154,0.0002049688,0.00004233837,0.00006138513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002483606,0.00003448151,0.000001830738,0.000003108127,9.364969e-7,5.53402e-7,0.00002721896,0.03437845,0.002765546,0.002789784,0.0006800251,0.9593156],"study_design_scores_gemma":[0.0002727991,0.00002591668,0.00000410743,0.000002986719,9.07326e-7,0.000001737983,0.000001358123,0.9734108,0.02390443,0.001419295,0.0008843807,0.00007126915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005042133,0.00001117253,0.9957211,0.001084674,0.0001021282,0.00007993018,3.118009e-7,0.0001713375,0.002778946],"genre_scores_gemma":[0.3216278,0.00000119742,0.6764534,0.0009408977,0.00001703956,0.000007424061,1.653177e-7,0.000003395446,0.0009486921],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9592443,"threshold_uncertainty_score":0.193138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04048236382330496,"score_gpt":0.274154542647475,"score_spread":0.23367217882417,"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."}}