{"id":"W4247602681","doi":"10.1007/978-3-030-62124-7_10","title":"Basic Video Compression Techniques","year":2021,"lang":"en","type":"book-chapter","venue":"Texts in computer science","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Motion compensation; Video compression picture types; Computer science; Redundancy (engineering); Data compression; Block-matching algorithm; Digital video; Computer vision; Artificial intelligence; Multiview Video Coding; Reference frame; Video processing; Quarter-pixel motion; Video tracking; Frame (networking); Telecommunications","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":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001146289,0.0007554226,0.0008557508,0.001365261,0.0003604892,0.0007401762,0.008338032,0.0004001098,0.0001226017],"category_scores_gemma":[0.00005770881,0.0007247051,0.000177166,0.0008099077,0.0009060153,0.002342817,0.009304545,0.001174284,0.0001069537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004375288,"about_ca_system_score_gemma":0.0007134171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001080473,"about_ca_topic_score_gemma":0.000008257207,"domain_scores_codex":[0.9937227,0.00007374227,0.0009452786,0.002677975,0.001719094,0.0008612444],"domain_scores_gemma":[0.99419,0.0002884303,0.0005361809,0.004213412,0.0004549179,0.0003170691],"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":[0.000002973844,0.00005342898,0.000006394801,0.00003765018,0.000004641714,0.0002855698,0.00008811122,0.00004844849,0.001165099,0.2634078,0.005706002,0.7291939],"study_design_scores_gemma":[0.0005045321,0.000363821,0.0001821447,0.006397197,0.0000135298,0.0003856957,0.000001667721,0.06298584,0.08716496,0.3353774,0.5036143,0.003008911],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000122642,0.0008022725,0.9279084,0.0003291809,0.001050041,0.0005523412,0.00001432633,0.0014912,0.06784004],"genre_scores_gemma":[0.002125664,0.0004319647,0.9697273,0.001387971,0.0003734729,0.00005642685,0.00002275794,0.00007822944,0.02579619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7261849,"threshold_uncertainty_score":0.9995204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222745907679123,"score_gpt":0.2875505278268679,"score_spread":0.2653230687500766,"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."}}