{"id":"W3008115664","doi":"10.1007/978-3-030-40783-4_18","title":"Linear Hashing Implementations for Flash Memory","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Hash function; Computer science; Flash memory; Hash table; Flash (photography); Linear hashing; Search engine indexing; Parallel computing; Universal hashing; Implementation; Memory management; Double hashing; Dynamic perfect hashing; Computer hardware; Semiconductor memory; Programming language; Information retrieval","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"],"consensus_categories":[],"category_scores_codex":[0.000223037,0.0003375605,0.0003409772,0.0004295735,0.0002994352,0.0006623514,0.0006205167,0.0002499993,0.0000151555],"category_scores_gemma":[0.0003431797,0.0003381595,0.000103901,0.000283168,0.00003547592,0.002879456,0.000192959,0.0004145758,0.00004566261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001371694,"about_ca_system_score_gemma":0.000382249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393389,"about_ca_topic_score_gemma":0.00003351807,"domain_scores_codex":[0.9983441,0.000009596745,0.0007209415,0.000306459,0.000360075,0.0002588248],"domain_scores_gemma":[0.9983753,0.0001773533,0.0005287912,0.0002921818,0.0005673883,0.00005896971],"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":[0.00002723088,0.000008632524,0.00001081539,0.001047043,0.00002676483,0.000004463764,0.002487114,0.01962627,0.00006508707,0.01900108,0.0003714098,0.9573241],"study_design_scores_gemma":[0.001892327,0.00006806047,0.00006162153,0.001883842,0.00009119841,0.00003585205,0.00004683562,0.8023655,0.0005901374,0.06064875,0.1307644,0.001551463],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001917797,0.0002856675,0.9824401,0.00342019,0.0004586038,0.000470788,0.00003329319,0.0002645278,0.01260767],"genre_scores_gemma":[0.471907,0.0003209976,0.4756507,0.03780641,0.003124645,0.0005449997,0.004414843,0.0003248728,0.005905476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9557726,"threshold_uncertainty_score":0.999907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799625538510061,"score_gpt":0.2597046319881146,"score_spread":0.231708376603014,"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."}}