{"id":"W4400909988","doi":"10.1109/icde60146.2024.00021","title":"KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science","year":2024,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Concordia University","funders":"","keywords":"Computer science; Abstraction; Automation; Software engineering; Data science; Programming language; Engineering; Epistemology","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":[0.003834244,0.00187955,0.00116671,0.004344549,0.001188826,0.004778788,0.005093928,0.001455447,0.008868001],"category_scores_gemma":[0.008836102,0.00196357,0.002813169,0.003260382,0.002238357,0.01065918,0.01073037,0.004699906,0.006690993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002050783,"about_ca_system_score_gemma":0.004380558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009890627,"about_ca_topic_score_gemma":0.009714397,"domain_scores_codex":[0.9969212,0.0005514672,0.0003291021,0.0008182176,0.00115072,0.0002293162],"domain_scores_gemma":[0.9949383,0.001528403,0.0004089476,0.002280466,0.0004762695,0.0003676536],"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":[0.002472951,0.0008285972,0.007858693,0.003512802,0.001053969,0.001527989,0.002779176,0.04166453,0.03179552,0.1782616,0.212437,0.5158072],"study_design_scores_gemma":[0.0004212385,0.0002705654,0.002570686,0.0005256308,0.0002521119,0.0008472414,0.0005079089,0.2715537,0.0540273,0.1861737,0.4824636,0.0003862365],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005090124,0.0006041324,0.711444,0.0006188345,0.0001736162,0.0004889999,0.005056557,0.2709234,0.005600246],"genre_scores_gemma":[0.0798411,0.001471832,0.8609086,0.001043073,0.00009370623,0.0008099894,0.03170947,0.01764471,0.006477481],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009890627,"threshold_uncertainty_score":0.02966642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06975662402876652,"score_gpt":0.3397223041992777,"score_spread":0.2699656801705111,"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."}}