{"id":"W4413915186","doi":"10.3390/photonics12090882","title":"High-Resolution Hogel Image Generation Using GPU Acceleration","year":2025,"lang":"en","type":"article","venue":"Photonics","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"123 Certification (Canada)","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea","keywords":"Computer science; Acceleration; Computer graphics (images); Image resolution; General-purpose computing on graphics processing units; Computer vision; Physics; Graphics","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":[0.00005723598,0.000107435,0.00009844803,0.0001014147,0.00008281482,0.00006381304,0.0001057394,0.00008394687,0.00001026479],"category_scores_gemma":[0.00007615565,0.0001194115,0.00002517864,0.0002301491,0.00004015898,0.0002984404,0.00004591603,0.0001547677,0.00001400612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002206159,"about_ca_system_score_gemma":0.00001705247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001159943,"about_ca_topic_score_gemma":0.00001203019,"domain_scores_codex":[0.9994427,0.00000739914,0.0001543567,0.0001419567,0.0000750433,0.0001785744],"domain_scores_gemma":[0.9996696,0.00001726398,0.00001784193,0.0002293093,0.00005008133,0.0000159147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002369354,0.00001058558,0.00002246828,0.00002426815,0.00001415978,0.000002443251,0.00001384576,0.314647,0.6707056,0.01007308,0.000745701,0.003738516],"study_design_scores_gemma":[0.0001106481,0.000003433079,0.00008722206,0.00001134725,0.00001157742,9.667567e-7,0.00000900488,0.7614105,0.2347314,0.002878464,0.0006569641,0.00008843275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3497483,0.0002801968,0.6476132,0.0001114597,0.0004405523,0.0001313968,0.00000454697,0.0009461341,0.0007242191],"genre_scores_gemma":[0.6833888,0.0001026266,0.3163472,0.00004752839,0.00002674117,0.00001675941,0.00001848202,0.0000163629,0.0000355162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4467636,"threshold_uncertainty_score":0.4869461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02249623084925867,"score_gpt":0.2690780366098056,"score_spread":0.2465818057605469,"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."}}