{"id":"W1973020953","doi":"10.1145/2554850.2554891","title":"LittleD","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; SQL; Joins; In-Memory Processing; Relational database; Parsing; Database; Stored procedure; Memory management; Query optimization; Relational database management system; Programming language; Query by Example; Information retrieval; Search engine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003264126,0.00110775,0.001187552,0.002895323,0.001201623,0.008294881,0.00568784,0.001899943,0.1074779],"category_scores_gemma":[0.01349953,0.001255217,0.001096145,0.003783694,0.001043076,0.009273768,0.005823669,0.002425078,0.08411778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001655588,"about_ca_system_score_gemma":0.002461073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002272997,"about_ca_topic_score_gemma":0.002474356,"domain_scores_codex":[0.9948349,0.0006488123,0.0005905333,0.00101766,0.002520398,0.0003877827],"domain_scores_gemma":[0.9888454,0.001957896,0.000453892,0.004391667,0.003561493,0.0007896851],"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":[0.0008803991,0.0002222807,0.002215351,0.001323574,0.00008383999,0.000334994,0.0003943454,0.001521132,0.009671103,0.07380375,0.4903206,0.4192286],"study_design_scores_gemma":[0.00008417921,0.00008324723,0.0005065034,0.000122634,0.00002559337,0.0004307351,0.00007740477,0.004998181,0.006544427,0.01236195,0.9747181,0.00004714152],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01088182,0.008260791,0.3867421,0.00749487,0.002850735,0.001167133,0.04432984,0.1831334,0.3551393],"genre_scores_gemma":[0.1005301,0.007849532,0.3792833,0.009251112,0.001591951,0.001440168,0.1620416,0.03613461,0.3018777],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8925221,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005119955166473913,"score_gpt":0.2038580278109582,"score_spread":0.1987380726444843,"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."}}