{"id":"W4400887584","doi":"10.24132/csrn.3401.1","title":"A Synergy of Computer Graphics and Generative AI: Advancements and Challenges","year":2024,"lang":"en","type":"article","venue":"Computer Science Research Notes","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Generative grammar; Computer graphics; Graphics; Computer graphics (images); Artificial intelligence; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007518928,0.0007696985,0.001006006,0.001893114,0.001314569,0.007488693,0.001701578,0.00404154,0.01119199],"category_scores_gemma":[0.01041661,0.0005117435,0.0005631791,0.001903396,0.007792609,0.01671002,0.005080618,0.008082005,0.003238811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420702,"about_ca_system_score_gemma":0.001511919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007920634,"about_ca_topic_score_gemma":0.001312148,"domain_scores_codex":[0.997188,0.001349061,0.00009607786,0.0003220515,0.0008240817,0.0002207447],"domain_scores_gemma":[0.9831835,0.01227675,0.0002712138,0.001753038,0.001321138,0.001194405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000559425,0.00004944696,0.0005260102,0.0004005428,0.00003030099,0.0000869503,0.0006232691,0.001550255,0.0004879003,0.7273366,0.04846464,0.2203881],"study_design_scores_gemma":[0.00001481823,0.00006416986,0.0003200211,0.0004005082,0.00001035725,0.0002977662,0.0007209416,0.006819837,0.0004303856,0.7215323,0.2693454,0.00004360262],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.01145713,0.3092478,0.1733963,0.3927657,0.009988472,0.00004092436,0.0002398211,0.0009072521,0.1019567],"genre_scores_gemma":[0.3894917,0.3180026,0.1911073,0.03077869,0.02864806,0.0001598352,0.0003734763,0.0009626043,0.04047587],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01119199,"threshold_uncertainty_score":0.0397644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146036469451965,"score_gpt":0.3789378779504285,"score_spread":0.264334231005232,"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."}}