{"id":"W2397620396","doi":"10.1201/9781003059325-10","title":"Using Stochastic Sampling to Create Depth-of-Field Effect in Real-Time Direct Volume Rendering","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Rendering (computer graphics); Volume rendering; Volume (thermodynamics); Computer graphics (images); Computer science; Real-time rendering; Physics","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":[0.0004265347,0.0004703857,0.0003101347,0.0003216643,0.0001638122,0.0007226655,0.0004787881,0.0003477053,0.002576125],"category_scores_gemma":[0.0008302591,0.0002763054,0.0004574005,0.0003635785,0.0003860555,0.0004569366,0.0005725403,0.0006784526,0.0006004534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003828446,"about_ca_system_score_gemma":0.0003536239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000801028,"about_ca_topic_score_gemma":0.001012444,"domain_scores_codex":[0.9997883,0.00004963547,0.000007933605,0.00002292023,0.0001166527,0.00001439631],"domain_scores_gemma":[0.9997116,0.0001550476,0.00002555635,0.00003953428,0.00004588598,0.00002240285],"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":[0.0001983927,0.0001202374,0.0007452429,0.0003281701,0.00005861823,0.0003212395,0.0004219264,0.1914036,0.4118887,0.07300772,0.006301827,0.3152042],"study_design_scores_gemma":[0.00003485651,0.0001211588,0.0005108716,0.00002490627,0.00001961104,0.00058352,0.00003126837,0.8941252,0.07097943,0.01016085,0.02336139,0.00004701406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007108616,0.0002620289,0.9891505,0.00004083659,0.00004858672,0.00002768214,0.00002142769,0.0004225469,0.002917829],"genre_scores_gemma":[0.1667973,0.000817886,0.8247582,0.00009587126,0.00006099023,0.00007415412,0.0001212179,0.0003370912,0.006937229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002576125,"threshold_uncertainty_score":0.008617938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06319135745197625,"score_gpt":0.3257661194746043,"score_spread":0.262574762022628,"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."}}