{"id":"W4244161838","doi":"10.1007/978-0-387-39940-9_3130","title":"Multi-Version Database","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Database; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007875893,0.0009431815,0.001375739,0.0005527367,0.0002055029,0.00006836966,0.001748434,0.0003907815,0.0001146852],"category_scores_gemma":[0.0001356744,0.0008815557,0.0003044691,0.0001792249,0.0001701033,0.002090567,0.001289784,0.0006864242,0.0007446485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162118,"about_ca_system_score_gemma":0.0003832412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003506434,"about_ca_topic_score_gemma":0.00006515719,"domain_scores_codex":[0.9948624,0.0001147803,0.001559946,0.00155758,0.001264924,0.000640413],"domain_scores_gemma":[0.9931543,0.0002172399,0.001382803,0.004479292,0.0003588854,0.000407509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004397397,0.0001930029,0.00002115296,0.001863717,0.0001969708,0.0007802506,0.0002866863,0.00007709838,0.0008631053,0.8647509,0.1168097,0.01411345],"study_design_scores_gemma":[0.0006666447,0.0001195243,0.000008029434,0.002318052,0.00006301093,0.0001018125,0.00003666893,0.001592466,0.00007683493,0.0001005713,0.9939774,0.0009390247],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.000006596394,0.009968842,0.5227727,0.00006364706,0.004034828,0.0014165,0.01304081,0.0004502424,0.4482458],"genre_scores_gemma":[0.0000887615,0.009316988,0.2433687,0.0001146714,0.001332632,0.00005957852,0.00813935,0.00017086,0.7374085],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8771676,"threshold_uncertainty_score":0.9993635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927047840469381,"score_gpt":0.2465602220159596,"score_spread":0.2272897436112658,"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."}}