{"id":"W4389747813","doi":"10.1109/tvcg.2023.3343166","title":"Cone-Traced Supersampling With Subpixel Edge Reconstruction","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Huawei Technologies (Canada)","funders":"","keywords":"Subpixel rendering; Computer science; Computer vision; Computer graphics (images); Artificial intelligence; Enhanced Data Rates for GSM Evolution; Visual hull; Iterative reconstruction; Visualization; Pixel","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":[0.0004438118,0.0006618861,0.0004706061,0.0007130406,0.0002211944,0.0008315987,0.0007997584,0.0005039395,0.003228515],"category_scores_gemma":[0.001524472,0.0003120994,0.0005019093,0.0005474039,0.0003492904,0.000695527,0.001006958,0.0007077422,0.0007785255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003822884,"about_ca_system_score_gemma":0.001126528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003002384,"about_ca_topic_score_gemma":0.00483437,"domain_scores_codex":[0.999571,0.00004147903,0.00001676331,0.00004983549,0.0002850971,0.00003565746],"domain_scores_gemma":[0.9994247,0.0001292168,0.00006342219,0.0001805919,0.0001627085,0.00003943649],"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":[0.0003539967,0.0001958613,0.002489665,0.0001792777,0.00005455016,0.000425314,0.00049264,0.2605803,0.1360853,0.04575784,0.006551791,0.5468336],"study_design_scores_gemma":[0.00001720361,0.00006325851,0.0002979338,0.000009139921,0.000006576134,0.0002049724,0.00003162749,0.9581283,0.03045095,0.004295575,0.006477189,0.00001727054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01047641,0.00003678417,0.9872143,0.00002194285,0.00001545381,0.00003474942,0.0000436399,0.000888594,0.001268053],"genre_scores_gemma":[0.1198961,0.00008675751,0.876967,0.00004107635,0.00001400493,0.00004961942,0.0002468745,0.0003686671,0.002329984],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003228515,"threshold_uncertainty_score":0.01080048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02599346872132217,"score_gpt":0.27885170196264,"score_spread":0.2528582332413178,"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."}}