{"id":"W4388758129","doi":"10.1109/uemcon59035.2023.10316126","title":"Efficient Cloud Pipelines for Neural Radiance Fields","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North; University of Victoria","funders":"","keywords":"Computer science; Radiance; Cloud computing; Pipeline (software); Pipeline transport; Geospatial analysis; Software portability; Representation (politics); Pascal (unit); Artificial neural network; Data science; Artificial intelligence; Remote sensing; Engineering; Programming language","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":[0.0004528232,0.00105893,0.0007641791,0.00100285,0.0009073815,0.001311409,0.002712799,0.0007645558,0.02557797],"category_scores_gemma":[0.002213193,0.0006286273,0.001337942,0.00148417,0.0004903869,0.00250596,0.001780112,0.001050381,0.005569359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001855801,"about_ca_system_score_gemma":0.001271311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0247276,"about_ca_topic_score_gemma":0.02623191,"domain_scores_codex":[0.9996707,0.00003337309,0.00001792451,0.00007136057,0.0001263692,0.00008036356],"domain_scores_gemma":[0.9993994,0.0002100469,0.00003904175,0.0001425125,0.0001537372,0.00005524188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001274107,0.0003512149,0.002915823,0.0003931602,0.000208565,0.0006840875,0.0004539051,0.2546342,0.04611281,0.03760449,0.06953348,0.5858341],"study_design_scores_gemma":[0.00008300506,0.00004586721,0.0003546678,0.00001009277,0.0000153095,0.0000919701,0.00005900609,0.9586262,0.0162033,0.01091782,0.01357015,0.00002259489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02237672,0.0003981068,0.9261181,0.0002990349,0.0001037205,0.0002040054,0.001093707,0.04299822,0.006408449],"genre_scores_gemma":[0.329959,0.0003851485,0.6470199,0.0002256489,0.00006779985,0.0002743275,0.005466894,0.004225906,0.01237536],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02557797,"threshold_uncertainty_score":0.08556682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03102867596317656,"score_gpt":0.317479315640941,"score_spread":0.2864506396777644,"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."}}