{"id":"W4408061126","doi":"10.14778/3705829.3705850","title":"Making CRDTs Not So Eventual","year":2024,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Toronto","funders":"","keywords":"Computer science","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":[0.01226514,0.0007273434,0.0008257043,0.0007705527,0.001892075,0.005287783,0.003207027,0.002052095,0.003771321],"category_scores_gemma":[0.03653413,0.001068742,0.00101073,0.0009597061,0.004194192,0.01122948,0.008562014,0.004514335,0.002223911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048165,"about_ca_system_score_gemma":0.00344528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001737601,"about_ca_topic_score_gemma":0.002223071,"domain_scores_codex":[0.9863133,0.003760369,0.001267039,0.001950402,0.00513071,0.00157811],"domain_scores_gemma":[0.953288,0.00773169,0.003279317,0.02731214,0.007085084,0.001303823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001527481,0.000418883,0.01213308,0.0009626742,0.000219705,0.001193837,0.003312296,0.06174547,0.08861133,0.5276653,0.0316144,0.2705956],"study_design_scores_gemma":[0.0004759376,0.0008142702,0.001489584,0.0002846101,0.0002554625,0.001129488,0.001293295,0.2569979,0.1412707,0.3278641,0.2678667,0.0002580755],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09797227,0.0005968872,0.865031,0.004002684,0.001081948,0.000379755,0.000319459,0.01320083,0.01741516],"genre_scores_gemma":[0.697713,0.000646929,0.2790518,0.001696368,0.0004422726,0.000450699,0.0007261527,0.002970561,0.01630226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01226514,"threshold_uncertainty_score":0.06486499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123369697432146,"score_gpt":0.2670379170096228,"score_spread":0.2458042200353014,"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."}}