{"id":"W4404955717","doi":"10.1109/micro61859.2024.00080","title":"Generalizing Ray Tracing Accelerators for Tree Traversals on GPUs","year":2024,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Science Foundation","keywords":"Computer science; Ray tracing (physics); Parallel computing; Tree (set theory); Tracing; Computer graphics (images); Computational science; Programming language; Mathematics; Physics; Combinatorics","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":[0.0004378408,0.0006238227,0.000438323,0.000613013,0.0004426877,0.001078254,0.001631974,0.0005777276,0.005569186],"category_scores_gemma":[0.00159995,0.0003793267,0.0009533677,0.001200254,0.0004114414,0.001253788,0.001122534,0.001391467,0.002027538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008171608,"about_ca_system_score_gemma":0.001367801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004914223,"about_ca_topic_score_gemma":0.005832861,"domain_scores_codex":[0.9996392,0.00003862572,0.00002776623,0.00005929645,0.000180386,0.00005476253],"domain_scores_gemma":[0.9993865,0.0001242133,0.00004502933,0.0001983741,0.0001885318,0.00005736629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000910746,0.0003185887,0.007245266,0.0004715374,0.0001811473,0.0004599984,0.0005344473,0.2482307,0.1465239,0.1276239,0.03224767,0.4352522],"study_design_scores_gemma":[0.00006924864,0.0001356769,0.0006454883,0.00002342308,0.00002977961,0.000145751,0.00003424952,0.9323564,0.02226788,0.009965858,0.03428956,0.00003672587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03316766,0.0003872938,0.9396241,0.0002570988,0.0002242039,0.0001361825,0.000185046,0.01343787,0.01258053],"genre_scores_gemma":[0.2735388,0.0005381012,0.7168843,0.000289143,0.00008587175,0.0002159722,0.0006352657,0.001154766,0.006657723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005569186,"threshold_uncertainty_score":0.0186308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04393482593106639,"score_gpt":0.3234320300776212,"score_spread":0.2794972041465548,"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."}}