{"id":"W4413361263","doi":"10.1109/icde65448.2025.00363","title":"LineageX: A Column Lineage Extraction System for SQL","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Column (typography); Computer science; SQL; Extraction (chemistry); Lineage (genetic); Database; Chromatography; Chemistry; Computer network","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":[0.002385877,0.001373069,0.0005887895,0.001837221,0.0008947696,0.002902266,0.002348334,0.0008466993,0.01790504],"category_scores_gemma":[0.008958633,0.001325361,0.001129844,0.001775026,0.0008224569,0.005965682,0.004140351,0.001994863,0.008499336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008898859,"about_ca_system_score_gemma":0.00244003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00497253,"about_ca_topic_score_gemma":0.006759749,"domain_scores_codex":[0.998602,0.0002214451,0.0001824604,0.0002940074,0.0006021524,0.000098007],"domain_scores_gemma":[0.9975386,0.0009210496,0.0002032375,0.0007244035,0.0004955361,0.0001172895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001585162,0.0003168097,0.01666049,0.001879248,0.0002689004,0.0009409538,0.003314572,0.00988421,0.03554692,0.0434266,0.5027959,0.3833802],"study_design_scores_gemma":[0.0003159255,0.0002234096,0.007337353,0.0004277269,0.0001102593,0.001111534,0.0007795331,0.2110573,0.09741912,0.0616718,0.6191935,0.0003525217],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.0067101,0.0002814506,0.3948268,0.0004062845,0.00008193536,0.0003261867,0.0218531,0.5696157,0.005898424],"genre_scores_gemma":[0.1071195,0.0008932492,0.6641602,0.001490637,0.00009772273,0.001144767,0.1111872,0.09658062,0.01732619],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01790504,"threshold_uncertainty_score":0.05989826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087692297055994,"score_gpt":0.2927652775393659,"score_spread":0.281888354568806,"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."}}