{"id":"W2368562647","doi":"","title":"Fast Mode Decison For H.264 Optimigation","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Discrete cosine transform; Motion estimation; Encoding (memory); Mode (computer interface); Quarter-pixel motion; Computation; Block (permutation group theory); Algorithm; Motion (physics); Data compression; Rate–distortion optimization; Real-time computing; Artificial intelligence; Computer vision; Block-matching algorithm; Video processing; Image (mathematics); Mathematics; Video tracking","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006639055,0.0006209228,0.0002843186,0.0007704326,0.000481655,0.0007080589,0.0006946927,0.0004816304,0.009756962],"category_scores_gemma":[0.001091998,0.0003184729,0.00024245,0.0004114594,0.0002084325,0.0006607774,0.0005236816,0.0007905354,0.002543112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004944114,"about_ca_system_score_gemma":0.0008904816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002889731,"about_ca_topic_score_gemma":0.006380423,"domain_scores_codex":[0.9997094,0.00005143893,0.0000175347,0.00004215462,0.0001386419,0.00004085089],"domain_scores_gemma":[0.9996167,0.00008355534,0.00002484524,0.00006062275,0.000195217,0.00001906439],"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":[0.0009247307,0.0001063053,0.0009937574,0.0002174502,0.00004426955,0.0001872439,0.0001615945,0.01102637,0.1360756,0.02077526,0.03059075,0.7988966],"study_design_scores_gemma":[0.0002848379,0.0005886196,0.002942316,0.0001233799,0.00005819591,0.0006023386,0.00009961433,0.5621736,0.3240935,0.01653004,0.09235322,0.0001503972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01790218,0.001135369,0.9631925,0.0002841829,0.0002446483,0.0002319949,0.0005189797,0.009574638,0.006915439],"genre_scores_gemma":[0.1458317,0.0006855778,0.8347287,0.0001925682,0.0001061801,0.0003009464,0.001512126,0.0007226609,0.01591959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009756962,"threshold_uncertainty_score":0.03264028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340569594304855,"score_gpt":0.2841167576281022,"score_spread":0.2707110616850536,"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."}}