{"id":"W6949194257","doi":"10.5281/zenodo.14053431","title":"ASPLOS 25' Artifact Evaluation for SCAR: Sub-Core and Atomic-Unit Collaborative Reduction for Efficient Raster-based Differentiable Rendering","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendering (computer graphics); Artifact (error); Visualization; Software; Reduction (mathematics)","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":[0.0009008144,0.001287942,0.0008835185,0.000705173,0.0005537838,0.002375023,0.001559032,0.0008762021,0.03653963],"category_scores_gemma":[0.001883709,0.0004789488,0.0007637459,0.0006730952,0.0004903327,0.001102069,0.001531034,0.00114054,0.007435485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007752255,"about_ca_system_score_gemma":0.001078832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002997763,"about_ca_topic_score_gemma":0.005640088,"domain_scores_codex":[0.999206,0.0001010412,0.00003013557,0.00006966978,0.0005240014,0.00006919607],"domain_scores_gemma":[0.9993516,0.0001855767,0.00003194923,0.0001797132,0.0002082849,0.00004294993],"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":[0.0007735838,0.0002449684,0.001077879,0.0004103039,0.0001393046,0.0004325564,0.0004284419,0.04339086,0.05518397,0.06147658,0.2180441,0.6183975],"study_design_scores_gemma":[0.0001605991,0.0001623486,0.000933377,0.00005546583,0.00003922329,0.0004422892,0.00008734743,0.7210526,0.1252913,0.01558158,0.1361136,0.00008014594],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01201458,0.0001914157,0.922765,0.0002275837,0.0001683189,0.0001046703,0.001154065,0.03713923,0.02623523],"genre_scores_gemma":[0.1385071,0.0001901024,0.8122889,0.0001857437,0.00005155024,0.0001542627,0.003801954,0.01515052,0.02966991],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03653963,"threshold_uncertainty_score":0.1222372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04104061284129041,"score_gpt":0.2669241886634559,"score_spread":0.2258835758221654,"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."}}