{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007516811,0.00136372,0.0009241377,0.002773061,0.001233011,0.004167621,0.004242794,0.001295128,0.02061949],"category_scores_gemma":[0.03051899,0.00123495,0.001436913,0.002681863,0.0009433199,0.008547587,0.005301037,0.002943319,0.01388595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087163,"about_ca_system_score_gemma":0.00361096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006125817,"about_ca_topic_score_gemma":0.006736564,"domain_scores_codex":[0.9945286,0.001419901,0.0005020675,0.001162887,0.002081987,0.0003045576],"domain_scores_gemma":[0.9815688,0.004972585,0.0007550186,0.009629085,0.002722675,0.0003518818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00126656,0.0003199846,0.005701913,0.001327676,0.0003054054,0.0006630374,0.001230403,0.01368299,0.009206719,0.08908156,0.2350552,0.6421586],"study_design_scores_gemma":[0.0002406931,0.0002947164,0.002376125,0.0003870695,0.0001347681,0.001668296,0.0003645623,0.1838328,0.02691809,0.09062997,0.6929849,0.0001681056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007015612,0.000871211,0.675166,0.001122661,0.0003667966,0.0005912742,0.01142882,0.2817685,0.0216691],"genre_scores_gemma":[0.09979133,0.001402481,0.8096693,0.0007256502,0.0001536875,0.0006327272,0.04238809,0.02375082,0.02148609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02061949,"threshold_uncertainty_score":0,"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."}}