{"id":"W4287509673","doi":"10.1145/3532719.3543238","title":"DynaPix: Normal Map Pixelization for Dynamic Lighting","year":2022,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Workflow; Computer graphics (images); Extension (predicate logic); Flexibility (engineering); Pixel; Computer vision; Game engine; Artificial intelligence; Multimedia; Database; Programming language; 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":[0.0004542707,0.00115114,0.0005523915,0.0009539942,0.0005635174,0.001813498,0.001695764,0.0005707173,0.0345897],"category_scores_gemma":[0.001891912,0.0008519832,0.000819086,0.0004792218,0.0005729254,0.001723667,0.002650285,0.001507332,0.008519842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004324777,"about_ca_system_score_gemma":0.0005356853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001741328,"about_ca_topic_score_gemma":0.003062023,"domain_scores_codex":[0.9996095,0.00003746234,0.0000203816,0.00007755835,0.0002044416,0.00005062426],"domain_scores_gemma":[0.9995829,0.0001297507,0.00002281525,0.0001135312,0.0001139445,0.00003709219],"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":[0.0005786191,0.0001445053,0.002563858,0.0008294955,0.0001008015,0.000616691,0.001422839,0.02081485,0.08921686,0.04324796,0.1343613,0.7061021],"study_design_scores_gemma":[0.0001723395,0.0001192341,0.002369995,0.000199892,0.00005530192,0.001519929,0.0004117722,0.2783492,0.1411982,0.04663663,0.528743,0.0002246219],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008252085,0.0001994534,0.8966122,0.0001349984,0.0001706222,0.0001206482,0.001026542,0.0794352,0.01404831],"genre_scores_gemma":[0.1542978,0.0005407692,0.7702644,0.0002711118,0.0000741754,0.0004116119,0.00394925,0.04864559,0.02154524],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0345897,"threshold_uncertainty_score":0.1157141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119907419169313,"score_gpt":0.2759094838012437,"score_spread":0.2647104096095506,"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."}}