{"id":"W2607340821","doi":"10.1002/cav.1755","title":"High‐fidelity iridal light transport simulations at interactive rates","year":2017,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rendering (computer graphics); Computer science; Fidelity; High fidelity; Visualization; Artificial intelligence; Telecommunications","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":[0.0004172231,0.0003645058,0.0005708688,0.0003451344,0.0006091276,0.0009183935,0.000988223,0.001042169,0.002915255],"category_scores_gemma":[0.002146021,0.0002606256,0.0004161774,0.0004023738,0.0007584571,0.0008292801,0.0006464716,0.0009423488,0.0002127445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008921293,"about_ca_system_score_gemma":0.0009346745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0101927,"about_ca_topic_score_gemma":0.004908968,"domain_scores_codex":[0.9998081,0.00003787406,0.000006324895,0.00001912076,0.00007140748,0.00005718239],"domain_scores_gemma":[0.9990485,0.000607663,0.00006923063,0.00008796011,0.0001261483,0.00006052546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009274791,0.0000891181,0.0008465318,0.00003466926,0.00001194782,0.00007724181,0.0001070897,0.9884403,0.003247249,0.005419866,0.0003888953,0.00124423],"study_design_scores_gemma":[0.00001033703,0.000009642988,0.00007731179,0.000002267053,0.000001338059,0.000003239266,0.00001462396,0.9987293,0.0007204062,0.0002993472,0.0001289168,0.00000325939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9157502,0.0001401974,0.05955901,0.0005863805,0.00005802432,0.0001008102,0.000563483,0.0004839238,0.02275796],"genre_scores_gemma":[0.991193,0.00005639283,0.00701337,0.00004502765,0.000007375531,0.00007439021,0.0001837416,0.00007830564,0.001348443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0101927,"threshold_uncertainty_score":0.02026671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02096014577949325,"score_gpt":0.3153127725169331,"score_spread":0.2943526267374398,"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."}}