{"id":"W2089058832","doi":"10.1109/icip.2011.6115637","title":"A structure-guided conditional sampling model for video resolution enhancement","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Sampling (signal processing); Computer vision; Resolution (logic); Binary number; Pattern recognition (psychology); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001251948,0.0001042829,0.00009167245,0.0000679053,0.0001404091,0.00004943157,0.0004490499,0.00003317368,0.00003262551],"category_scores_gemma":[0.00005668702,0.00009607165,0.00003534681,0.000097434,0.00003756718,0.000747523,0.000136911,0.00005646803,0.000003303805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006421973,"about_ca_system_score_gemma":0.00007443346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000044858,"about_ca_topic_score_gemma":0.00000301776,"domain_scores_codex":[0.9990965,0.000008240369,0.0001997711,0.0003251607,0.0001537489,0.0002166261],"domain_scores_gemma":[0.9993557,0.00002820395,0.00009070199,0.000293752,0.0001874224,0.00004426274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003067579,0.00009145758,0.00001711574,0.00005052059,0.00001852673,0.000001177086,0.001013405,0.001214257,0.1614426,0.818889,0.005482066,0.01174916],"study_design_scores_gemma":[0.00008725239,0.0000215444,0.00001363267,0.00000675095,0.000001558872,0.000003473931,0.000001675639,0.503602,0.08325754,0.4128236,0.0001058888,0.00007511748],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002810993,0.00002659888,0.9978268,0.00009778406,0.00005418467,0.0002319067,0.000007565114,0.0004384355,0.001035657],"genre_scores_gemma":[0.2356333,0.000001122841,0.7635285,0.0005700162,0.00001728235,0.00006603511,0.0000075311,0.000006381855,0.0001698345],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5023877,"threshold_uncertainty_score":0.3917688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1275105843325405,"score_gpt":0.3423396137892457,"score_spread":0.2148290294567052,"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."}}