{"id":"W2119530237","doi":"10.5281/zenodo.40733","title":"A Colour Correction Preprocessing Method For Multiview Video Coding","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Preprocessor; Data compression; Coding (social sciences); Matching (statistics); Pixel; Pattern recognition (psychology); Mathematics; Statistics","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":[0.000459459,0.0008810015,0.0007045701,0.001566361,0.0004179926,0.0008968022,0.00098026,0.000743503,0.006569662],"category_scores_gemma":[0.001281689,0.0004611839,0.001009292,0.001160448,0.0003166992,0.0007788289,0.0007329838,0.001212189,0.002748175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004673423,"about_ca_system_score_gemma":0.0008777693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005817886,"about_ca_topic_score_gemma":0.007692396,"domain_scores_codex":[0.9996418,0.00003748298,0.000020449,0.00006369167,0.0001922392,0.00004436001],"domain_scores_gemma":[0.99935,0.0001208886,0.00003602889,0.0001131871,0.0003515213,0.00002841131],"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":[0.000266007,0.00007760942,0.0003164609,0.0001722187,0.00006249529,0.00007077748,0.00003881272,0.007671544,0.2463386,0.00347081,0.00686136,0.7346533],"study_design_scores_gemma":[0.00005475725,0.0001760328,0.002941556,0.00005390493,0.0001608349,0.000608671,0.00004475896,0.5196064,0.4408253,0.003764736,0.0316758,0.00008717966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005058739,0.0005518579,0.9919391,0.00008885936,0.0002145708,0.00003979903,0.0001244593,0.001106665,0.0008758824],"genre_scores_gemma":[0.04724041,0.0008093331,0.9440175,0.00009158398,0.0001273206,0.00006117075,0.0006876457,0.0003419635,0.006623048],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006569662,"threshold_uncertainty_score":0.02197766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05045763243784831,"score_gpt":0.3695995918141401,"score_spread":0.3191419593762919,"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."}}