{"id":"W2952776792","doi":"10.48550/arxiv.1208.0084","title":"Fundamentals of Order Dependencies","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Lexicographical order; Functional dependency; Axiom; Tuple; Dependency theory (database theory); Computer science; Inference; Dependency (UML); Set (abstract data type); Query optimization; Theoretical computer science; Order (exchange); Rule of inference; Mathematics; Data mining; Discrete mathematics; Relational database; Artificial intelligence; Programming language; Combinatorics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001988197,0.0002321881,0.0003425142,0.0001448068,0.0000852809,0.00002356861,0.0009446599,0.0001548724,0.00006148799],"category_scores_gemma":[0.00002444259,0.0002445507,0.0001275523,0.0003702867,0.0001264245,0.0007160756,0.002508581,0.0002547388,0.00006482166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000900978,"about_ca_system_score_gemma":0.0001448343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002982224,"about_ca_topic_score_gemma":0.00006332837,"domain_scores_codex":[0.9987214,0.00008216003,0.0002129183,0.0005846339,0.0001019698,0.0002968876],"domain_scores_gemma":[0.9980883,0.00006285613,0.0003296705,0.001229589,0.0001685253,0.0001210643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001235859,0.00008754274,0.004565875,0.0002097033,0.00008892831,0.00006411575,0.0004163606,0.01511136,0.0003005821,0.9783045,0.0002229476,0.0006157102],"study_design_scores_gemma":[0.007369454,0.0007726212,0.03005092,0.003856981,0.001103954,0.0002367213,0.007451489,0.383415,0.04466809,0.2465117,0.2624017,0.01216133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09433131,0.0002969348,0.9015106,0.00001825139,0.0006795307,0.0001844536,0.0000706268,0.0001137339,0.002794563],"genre_scores_gemma":[0.9803119,0.0001246752,0.01801392,0.0000274619,0.00005643036,8.063155e-7,0.00001975704,0.0000110598,0.001433975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8859806,"threshold_uncertainty_score":0.9972487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08898652615790204,"score_gpt":0.197886085240735,"score_spread":0.108899559082833,"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."}}