{"id":"W2965906602","doi":"10.1145/3335783.3335800","title":"Improvement of SQL Recommendation on Scientific Database","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; SQL; Session (web analytics); Tuple; Information retrieval; Query by Example; Recommender system; Database; World Wide Web; Search engine; Web search query","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003957271,0.001048884,0.001110572,0.002445086,0.0005104024,0.001560284,0.001124376,0.0008473413,0.002221646],"category_scores_gemma":[0.01496258,0.0004050946,0.0008458187,0.002937162,0.0001697372,0.002677087,0.0006555929,0.0008374993,0.001898614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005667504,"about_ca_system_score_gemma":0.001020689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01241374,"about_ca_topic_score_gemma":0.02221643,"domain_scores_codex":[0.9972186,0.0006790484,0.0003025161,0.0005269684,0.001153291,0.0001195802],"domain_scores_gemma":[0.990694,0.002785135,0.0005019862,0.002176037,0.003590763,0.0002521395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001064508,0.0007470963,0.03635205,0.001024615,0.0003874103,0.0002520882,0.0005762744,0.02914405,0.03710531,0.001887296,0.04264272,0.8488166],"study_design_scores_gemma":[0.0002398573,0.001299624,0.03553294,0.0001055563,0.0004229603,0.0006964065,0.000733291,0.8663322,0.04472988,0.003777356,0.04596975,0.0001601857],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2980467,0.008255526,0.6341327,0.00147767,0.000319304,0.0007706618,0.0105473,0.03750607,0.008943969],"genre_scores_gemma":[0.4357362,0.002744093,0.5374417,0.0003884402,0.0001631995,0.0001708087,0.01745794,0.0004557081,0.005441869],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01241374,"threshold_uncertainty_score":0.02468294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373827164399546,"score_gpt":0.2502169216144368,"score_spread":0.2364786499704414,"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."}}