{"id":"W2014888296","doi":"10.14778/1920841.1921003","title":"TRAMP","year":2010,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Provenance; Computer science; Schema (genetic algorithms); Transformation (genetics); Debugging; Tracing; Tramp; Suite; Information retrieval; Programming language; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003864425,0.00009445004,0.0001451028,0.0001369994,0.0001697291,0.0003157633,0.00219537,0.00002917763,0.0003934624],"category_scores_gemma":[0.002025168,0.00005051715,0.0001279522,0.0007446412,0.000142359,0.0001879196,0.0008500804,0.0001617018,0.0001425482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001170513,"about_ca_system_score_gemma":0.00001702233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002412139,"about_ca_topic_score_gemma":0.000009241057,"domain_scores_codex":[0.9974524,0.000006225912,0.0004404167,0.0004397375,0.001450611,0.0002105567],"domain_scores_gemma":[0.9986749,0.0001542416,0.0002952448,0.0005110643,0.0002940522,0.00007047343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002563999,0.0002715513,0.02726236,0.00002015317,0.00003292734,4.223265e-7,0.001063976,0.00002512152,0.1706292,0.1453754,0.4778617,0.1774316],"study_design_scores_gemma":[0.0006440273,0.0000660258,0.05004142,0.00003479991,0.00003295152,0.00001506476,0.00135998,0.002072644,0.1495566,0.1363039,0.6596014,0.0002711912],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9066228,0.00001222042,0.00008054212,0.00359094,0.002717847,0.0002717371,0.000007740257,0.0000437708,0.0866524],"genre_scores_gemma":[0.9903229,0.000001043329,0.001619519,0.0001650548,0.00009077456,0.000008170529,2.868489e-7,0.000004778271,0.007787457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1817396,"threshold_uncertainty_score":0.4308138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07102342555161244,"score_gpt":0.3438698995370234,"score_spread":0.272846473985411,"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."}}