{"id":"W1753806996","doi":"10.1109/mwscas.1998.759423","title":"An adaptive virtual re-partitioning-based windowing technique for motion compensation","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Blocking (statistics); Pixel; Reduction (mathematics); Compensation (psychology); Computer vision; Variable (mathematics); Algorithm; Motion compensation; Artificial intelligence; Mathematics","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":[0.0001843355,0.0005480212,0.0004175888,0.0004452694,0.000261138,0.0003164707,0.0008394232,0.0003835255,0.001468211],"category_scores_gemma":[0.0004846125,0.0002771581,0.0005189073,0.0005158999,0.0002224301,0.0007382083,0.000429133,0.0007799267,0.0004808426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001661864,"about_ca_system_score_gemma":0.000238698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008265363,"about_ca_topic_score_gemma":0.001445178,"domain_scores_codex":[0.9998331,0.00002507693,0.00001214643,0.000036819,0.00007403285,0.00001881851],"domain_scores_gemma":[0.9998272,0.0000515524,0.00001933009,0.00004382282,0.00004607253,0.00001195541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002095426,0.00006374792,0.0002576299,0.0001902592,0.00007187085,0.000125479,0.0001121306,0.01220421,0.5147923,0.007349213,0.002471575,0.462152],"study_design_scores_gemma":[0.0000750713,0.0005838454,0.001921326,0.00004162709,0.0002122695,0.001729591,0.00005181731,0.558838,0.3790496,0.003655306,0.05372896,0.0001126435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009968243,0.0009866896,0.9876457,0.00004001668,0.00009856789,0.00004850541,0.00002830451,0.0004204823,0.0007635329],"genre_scores_gemma":[0.09946433,0.001099758,0.895688,0.00006641298,0.00009961236,0.00009246313,0.0001304987,0.0001285018,0.003230537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001468211,"threshold_uncertainty_score":0.004911661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042882194111858,"score_gpt":0.289282421621871,"score_spread":0.2488535996807524,"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."}}