{"id":"W7019610485","doi":"","title":"Hardware Architectures for Lossless Compression","year":2022,"lang":"en","type":"other","venue":"eScholarship (California Digital Library)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Huffman coding; Lossless compression; Lossy compression; Encoder; Data compression; Canonical Huffman code; Throughput; Encoding (memory)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001203337,0.0006452937,0.0005805322,0.0004742142,0.0003286198,0.002262633,0.003587378,0.0003293013,0.004778308],"category_scores_gemma":[0.00008665049,0.0005474584,0.0003496768,0.0004325171,0.00008141546,0.0009382081,0.003246547,0.0008059327,0.0007189949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003982787,"about_ca_system_score_gemma":0.0001595202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005331746,"about_ca_topic_score_gemma":0.000001013714,"domain_scores_codex":[0.9968315,0.0001151587,0.00044349,0.001225916,0.0007253315,0.0006585767],"domain_scores_gemma":[0.9974403,0.0002134173,0.0003778817,0.001581898,0.0000220973,0.0003644236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004160429,0.0001619304,0.000772266,0.000190775,0.00005823898,0.00005002423,0.00001253933,0.00002197845,0.000006885994,0.002381604,0.940505,0.05579716],"study_design_scores_gemma":[0.0005588442,0.00009286314,0.00006920577,0.0002524244,0.00001199365,0.0000171163,0.000004744794,0.001398258,0.0001055058,0.007902325,0.9888692,0.0007175503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002052394,0.004952325,0.204534,0.001124578,0.002184,0.002763615,0.08360859,0.006050659,0.694577],"genre_scores_gemma":[0.004043856,0.00009455494,0.126627,0.003169234,0.00258449,0.0008413144,0.02622803,0.00290406,0.8335075],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1389304,"threshold_uncertainty_score":0.9996977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395810215422786,"score_gpt":0.2259091941780104,"score_spread":0.2119510920237825,"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."}}