{"id":"W4283078428","doi":"10.1145/3550454.3555519","title":"Gaussian Blue Noise","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Gaussian; Noise (video); Computer science; Gaussian noise; Selection (genetic algorithm); Sampling (signal processing); Mathematical optimization; Quality (philosophy); Algorithm; Current (fluid); Mathematics; Artificial intelligence; Physics; Telecommunications","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":[0.0001912297,0.0001295429,0.0001042829,0.0004919777,0.0007017468,0.00006097107,0.001359307,0.00005803434,0.000154719],"category_scores_gemma":[0.00001944697,0.0001435245,0.0001114078,0.001488819,0.00005140064,0.0002072544,0.00004091118,0.0005402091,0.00001343518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005845553,"about_ca_system_score_gemma":0.0000518461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001486797,"about_ca_topic_score_gemma":0.000004508218,"domain_scores_codex":[0.998753,0.00007539262,0.0001856814,0.0003519398,0.0004141933,0.0002197808],"domain_scores_gemma":[0.998561,0.0001201375,0.00005917256,0.001124325,0.00004652817,0.00008880415],"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":[0.00004381308,0.001400821,0.0001355713,0.00001984724,0.000125486,0.00004894811,0.00328688,0.1253712,0.0003787757,0.7966241,0.003834219,0.06873029],"study_design_scores_gemma":[0.002763526,0.00329035,0.001864602,0.0000570122,0.0001430106,0.0004915737,0.0007702848,0.5250672,0.01471498,0.3789556,0.06937543,0.002506379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006248025,0.00002103414,0.9937788,0.003770635,0.0004987328,0.0002002939,0.00001832681,0.0007074004,0.0003800267],"genre_scores_gemma":[0.8383304,0.00003242655,0.1587707,0.002249343,0.00001357344,0.0003156806,0.000005895713,0.00002227497,0.0002596703],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8377057,"threshold_uncertainty_score":0.5852759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01945842353114328,"score_gpt":0.2441957438250686,"score_spread":0.2247373202939253,"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."}}