{"id":"W4396573125","doi":"10.5220/0012558100003690","title":"EmbedDB: A High-Performance Time Series Database for Embedded Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Series (stratigraphy); Database","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":[0.001187799,0.00176368,0.001525978,0.002184122,0.000390862,0.001804724,0.002851925,0.0007594451,0.02301153],"category_scores_gemma":[0.005875685,0.0007486324,0.0006997422,0.002289313,0.0002751125,0.002286633,0.00169269,0.001361899,0.01185262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004504259,"about_ca_system_score_gemma":0.0008481187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003375252,"about_ca_topic_score_gemma":0.004228404,"domain_scores_codex":[0.9990657,0.0001094998,0.0001523103,0.0002136095,0.0003881227,0.00007077411],"domain_scores_gemma":[0.998071,0.0005323141,0.0001588898,0.0006407179,0.0003717089,0.0002254462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.007135171,0.0008672859,0.01012297,0.002818935,0.001036357,0.001119837,0.0004579936,0.03531106,0.05861401,0.01164541,0.532719,0.3381519],"study_design_scores_gemma":[0.002820622,0.001186155,0.01674332,0.0002699099,0.0006869857,0.001070232,0.0002317802,0.4107892,0.1065426,0.02000087,0.4391712,0.0004871731],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.04703978,0.003129829,0.2708456,0.0006874653,0.000941304,0.0008842033,0.2348464,0.4313529,0.01027262],"genre_scores_gemma":[0.2621296,0.0028304,0.2302267,0.0009112901,0.0003346899,0.001484591,0.4563483,0.02797245,0.01776203],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02301153,"threshold_uncertainty_score":0.07698125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170328063546872,"score_gpt":0.2245472884395177,"score_spread":0.212844007804049,"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."}}