{"id":"W7131286450","doi":"10.1109/vcip67698.2025.11396899","title":"LiV: Live DASH Streaming for Volumetric Video","year":2025,"lang":"","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Encoder; High fidelity; Encoding (memory); Bandwidth (computing); Data compression; Dynamic Adaptive Streaming over HTTP; Ranging; Fidelity; Codec","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":[0.0006405923,0.0006089592,0.0003473832,0.0005966694,0.0003355193,0.0009512677,0.001356765,0.0004616529,0.006181824],"category_scores_gemma":[0.002160673,0.0001637368,0.0002197232,0.0004043456,0.0003718921,0.001105967,0.001498233,0.0008384598,0.001487292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244723,"about_ca_system_score_gemma":0.0004984466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002047884,"about_ca_topic_score_gemma":0.001553237,"domain_scores_codex":[0.9995438,0.00006349584,0.00002739682,0.00005548499,0.0002555783,0.00005414988],"domain_scores_gemma":[0.9993394,0.0001439441,0.00004556967,0.0001235682,0.0002499663,0.00009755437],"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":[0.002738719,0.0005951293,0.005357293,0.0008781595,0.000124163,0.001484064,0.0007890655,0.01664238,0.2409017,0.01401209,0.06055909,0.6559181],"study_design_scores_gemma":[0.0007240136,0.001813401,0.006936935,0.0002229106,0.00009416285,0.002591639,0.0006804781,0.519814,0.2929168,0.01175926,0.1621489,0.0002975162],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1384268,0.001488812,0.6988556,0.0006232479,0.0005639749,0.001497422,0.002893866,0.1213642,0.03428609],"genre_scores_gemma":[0.7910005,0.0009696166,0.1747362,0.0005729818,0.0001892601,0.0005404625,0.007121244,0.003089869,0.0217799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006181824,"threshold_uncertainty_score":0.02068031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042470325330795,"score_gpt":0.3430409904703146,"score_spread":0.3126162872170066,"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."}}