{"id":"W1918522533","doi":"10.1109/icde.2000.839445","title":"Mining recurrent items in multimedia with progressive resolution refinement","year":2002,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Alberta","funders":"","keywords":"Computer science; Completeness (order theory); Resolution (logic); Data mining; Visualization; Information retrieval; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003007883,0.0007414642,0.001185866,0.005330466,0.0004686874,0.001402106,0.00172819,0.0008881442,0.0006711189],"category_scores_gemma":[0.0170099,0.0006170351,0.001490795,0.003745202,0.000680002,0.002187068,0.001222072,0.000946058,0.0005587909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003327315,"about_ca_system_score_gemma":0.000602367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002205988,"about_ca_topic_score_gemma":0.002759577,"domain_scores_codex":[0.9979818,0.0005191173,0.0002820043,0.0003815609,0.0007089236,0.0001266114],"domain_scores_gemma":[0.9908993,0.00499952,0.001201448,0.0012206,0.001529136,0.0001499435],"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":[0.0007519656,0.0004027819,0.01852436,0.0006561247,0.0004215543,0.001302465,0.001146079,0.1152824,0.05930386,0.009007686,0.002409007,0.7907918],"study_design_scores_gemma":[0.0001028366,0.0005021536,0.007700746,0.00009402661,0.0003268731,0.001367109,0.000617129,0.9253314,0.03632456,0.02337549,0.004178104,0.00007958191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07404933,0.000692091,0.9234599,0.0001475599,0.00001751275,0.0002092873,0.0002984566,0.0006517324,0.0004741696],"genre_scores_gemma":[0.2186516,0.0004339659,0.7787693,0.00006366557,0.00004791936,0.0001814215,0.001254481,0.00004753144,0.0005501293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005330466,"threshold_uncertainty_score":0.01590741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293325271457795,"score_gpt":0.2327635748267603,"score_spread":0.2098303221121823,"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."}}