{"id":"W2107314054","doi":"10.1109/asic.2000.880711","title":"Using computational RAM for volume rendering","year":2002,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; SIMD; Memory bandwidth; Rendering (computer graphics); Parallel computing; Static random-access memory; Workstation; Computer hardware; Computer architecture; Computer graphics (images); Operating system","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":[0.00009758111,0.00006723246,0.0000724347,0.0001108239,0.0001229771,0.000163756,0.0002995056,0.00002688399,0.00003965773],"category_scores_gemma":[0.000006788036,0.00006809486,0.00005201011,0.0002480825,0.00001268075,0.0002541272,0.0001076159,0.00002817887,0.000004740266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001521548,"about_ca_system_score_gemma":0.000007937224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005841263,"about_ca_topic_score_gemma":5.726714e-7,"domain_scores_codex":[0.9993951,0.00001166371,0.0001438616,0.0002009169,0.0001194521,0.000128985],"domain_scores_gemma":[0.9996183,0.00003625092,0.00004142301,0.000166575,0.00009797062,0.00003950096],"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":[2.825869e-7,0.00003305773,0.0002018945,0.000007096326,0.000006276193,5.815912e-7,0.0001330657,0.001778189,0.00003710009,0.9775594,0.006133626,0.01410941],"study_design_scores_gemma":[0.0001025466,0.00002952072,0.0000955557,0.000004950965,0.000001106879,0.000006433801,0.000001595891,0.9603369,0.0001717333,0.03052194,0.008633315,0.00009435513],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004666153,0.00003300611,0.9979143,0.0002077397,0.0001178652,0.0001170634,9.373718e-7,0.0004017893,0.0007407333],"genre_scores_gemma":[0.3481221,0.000003132787,0.6512209,0.0003431352,0.00003902854,0.000007264999,0.000001800609,0.000005522106,0.000257085],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9585587,"threshold_uncertainty_score":0.2776828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067964286053889,"score_gpt":0.3335104736782802,"score_spread":0.2267140450728913,"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."}}