{"id":"W2011793254","doi":"10.1145/2766992","title":"Adaptive rendering with linear predictions","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Rendering (computer graphics); Pixel; Computer science; Algorithm; Linear model; Ground truth; Artificial intelligence; Global illumination; Machine learning","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":[0.0001952779,0.0001630472,0.0001281887,0.0004489643,0.0002456766,0.00009338943,0.0007338195,0.00008228938,0.000003225678],"category_scores_gemma":[0.00001109431,0.0001452951,0.00007728766,0.001483036,0.00007491779,0.0004486953,0.00002221699,0.0002785925,0.00000630931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003108883,"about_ca_system_score_gemma":0.0001079018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003326412,"about_ca_topic_score_gemma":0.00005275026,"domain_scores_codex":[0.9988193,0.00005218077,0.0001858597,0.0003632407,0.0003770717,0.0002023267],"domain_scores_gemma":[0.9985011,0.00007412856,0.00006157495,0.0009129239,0.0002648721,0.0001853753],"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":[0.0000642977,0.0006176013,0.0003634225,0.00001333334,0.0001834465,0.00002333657,0.002176612,0.005806274,0.00001301469,0.9689972,0.00119824,0.02054317],"study_design_scores_gemma":[0.001128228,0.002517425,0.0008012442,0.0001106313,0.00005142716,0.00009617927,0.0001915051,0.8997481,0.002622639,0.07938315,0.01267676,0.0006726689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006380978,0.00002804123,0.9971223,0.0005344723,0.000220195,0.0001599756,0.000007742981,0.0009151784,0.0003739303],"genre_scores_gemma":[0.8648689,0.00008641542,0.1343928,0.0004675461,0.00003827399,0.00006022088,0.000003376224,0.00002009617,0.0000623289],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8939419,"threshold_uncertainty_score":0.5924963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06121532519200461,"score_gpt":0.2908885305530646,"score_spread":0.22967320536106,"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."}}