{"id":"W3082442121","doi":"10.48550/arxiv.2005.06126","title":"Coded Caching Schemes with Linear Subpacketizations","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Transmission (telecommunications); Scheme (mathematics); Hamming distance; Code (set theory); Hamming code; Transmission rate; Computer network; Algorithm; Decoding methods; Block code; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006913343,0.0005194672,0.0004896543,0.0006291097,0.0005780121,0.001402243,0.001052894,0.0007092137,0.001836977],"category_scores_gemma":[0.004911585,0.0002672723,0.0002684959,0.001210629,0.0008922219,0.00219861,0.001243112,0.000899296,0.0005080614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478479,"about_ca_system_score_gemma":0.001030729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001859527,"about_ca_topic_score_gemma":0.001385985,"domain_scores_codex":[0.9990199,0.0002525979,0.00009314747,0.0001470095,0.000304858,0.0001824724],"domain_scores_gemma":[0.9960911,0.001197919,0.0003489511,0.00117138,0.001031909,0.0001587303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001183229,0.0002672322,0.001889282,0.0004213207,0.00007023257,0.0003349688,0.0005871602,0.2134791,0.1167647,0.3950847,0.004722757,0.2651953],"study_design_scores_gemma":[0.00009716272,0.0004334998,0.0005735573,0.0000545231,0.00004784466,0.0004019444,0.0001377804,0.8367584,0.08062803,0.06926022,0.01149998,0.0001069581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09867088,0.0005390116,0.893389,0.000212151,0.00009451016,0.0001509105,0.0001584956,0.0007273809,0.006057668],"genre_scores_gemma":[0.766308,0.0004316274,0.2271769,0.0002046573,0.00005675907,0.0002534745,0.0001903727,0.00008625977,0.005292039],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001859527,"threshold_uncertainty_score":0.01072717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09031361242499604,"score_gpt":0.1815463853952118,"score_spread":0.09123277297021572,"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."}}