{"id":"W2070192464","doi":"10.1109/wowmom.2013.6583407","title":"Encoding and communication energy consumption trade-off in H.264/AVC based video sensor network","year":2013,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Encoder; Real-time computing; Data compression; Wireless sensor network; Energy consumption; Video quality; Scalable Video Coding; Coding (social sciences); Encoding (memory); Computer network; Embedded system; Motion compensation; Engineering","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":[0.0002171805,0.0001128397,0.0001394822,0.0001250697,0.000146474,0.0001891632,0.0005821498,0.00009869697,0.00004081915],"category_scores_gemma":[0.00003774318,0.00009676882,0.00002439604,0.0002490737,0.00006826907,0.0004057992,0.0002751541,0.0001397947,0.00001647331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002586231,"about_ca_system_score_gemma":0.00001533004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001614643,"about_ca_topic_score_gemma":0.00004375582,"domain_scores_codex":[0.9990253,0.0001317405,0.0002230596,0.0002672357,0.0001240909,0.00022861],"domain_scores_gemma":[0.9989251,0.0003021181,0.00007424763,0.0006304368,0.0000219703,0.00004610407],"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":[0.000006794603,0.00008132594,0.01669172,0.00002386127,0.000009946045,0.000004648674,0.0002887378,0.002088312,0.004485373,0.1446222,0.01269158,0.8190055],"study_design_scores_gemma":[0.0006202485,0.00006095948,0.03074693,0.0002041714,0.000003332487,0.00001191552,0.0001221917,0.9327922,0.009155922,0.02060893,0.005330629,0.000342613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2014709,0.003310705,0.7686352,0.01907,0.0002502925,0.0003895789,6.091813e-7,0.001947594,0.004925083],"genre_scores_gemma":[0.9496713,0.0004571166,0.04906154,0.0006574309,0.00001108906,0.00003934556,0.000001346675,0.000004940102,0.00009588405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9307039,"threshold_uncertainty_score":0.3946118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297626099104647,"score_gpt":0.2350763446204807,"score_spread":0.2121000836294343,"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."}}