{"id":"W2898297547","doi":"10.1145/3276945.3276951","title":"HorseIR: bringing array programming languages together with database query processing","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Relational database management system; Compiler; SQL; Parallel computing; Database; Programming language; Relational database; Query optimization; Query plan; Bottleneck; Optimizing compiler; Sargable; Information retrieval; Web search query; 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":[],"consensus_categories":[],"category_scores_codex":[0.002231616,0.001061577,0.0006644562,0.0008457107,0.0004990781,0.002591878,0.003151283,0.0007924092,0.003114458],"category_scores_gemma":[0.004399054,0.0007918676,0.001387003,0.001029645,0.001590363,0.004386412,0.002781834,0.002684302,0.001249863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007810255,"about_ca_system_score_gemma":0.001431093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001896359,"about_ca_topic_score_gemma":0.002096092,"domain_scores_codex":[0.9978974,0.0003884037,0.0002388684,0.0004870633,0.0007349284,0.0002532786],"domain_scores_gemma":[0.9975678,0.0008661494,0.0002136186,0.000822754,0.0004193561,0.0001103781],"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":[0.001621322,0.0008115554,0.009007652,0.001211133,0.0002631751,0.001022488,0.002232362,0.09218536,0.09378499,0.151826,0.05422145,0.5918125],"study_design_scores_gemma":[0.0002518719,0.0008690331,0.001954167,0.0002026218,0.0002523764,0.0006655706,0.0004608051,0.5583472,0.2147803,0.09358828,0.1283874,0.000240422],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01658933,0.0002768119,0.9283779,0.0003360308,0.0001301703,0.0001236123,0.000295053,0.04983134,0.004039822],"genre_scores_gemma":[0.1397633,0.0004249897,0.8392771,0.0007581057,0.0001205936,0.0002418657,0.002078707,0.01202187,0.005313477],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.003151283,"threshold_uncertainty_score":0.01180202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204247686158018,"score_gpt":0.2679192914785732,"score_spread":0.2558768146169931,"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."}}