{"id":"W2789592939","doi":"10.5441/002/edbt.2018.87","title":"FastOFD: Contextual Data Cleaning with Ontology Functional Dependencies","year":2018,"lang":"en","type":"article","venue":"Movebank","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University; University of Waterloo; McMaster University","funders":"","keywords":"Computer science; Ontology; Functional dependency; Dependency theory (database theory); Information retrieval; Data mining; Relational database","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":[0.005501283,0.002088453,0.00157022,0.005539618,0.001772235,0.004500578,0.002708057,0.001572804,0.01180254],"category_scores_gemma":[0.02436063,0.001916861,0.003252924,0.004010705,0.001078045,0.006142335,0.007785209,0.002538079,0.004821577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001189814,"about_ca_system_score_gemma":0.004438126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188191,"about_ca_topic_score_gemma":0.01687667,"domain_scores_codex":[0.9952456,0.0008593911,0.0005908396,0.00120679,0.001779723,0.0003175626],"domain_scores_gemma":[0.9893194,0.003443562,0.0005586906,0.005235686,0.001262295,0.0001804309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000898383,0.0003731871,0.0119746,0.003541722,0.001093451,0.0008003453,0.001694321,0.02222847,0.01356815,0.05876842,0.3709923,0.5140667],"study_design_scores_gemma":[0.0002257617,0.0001551794,0.00650938,0.000978058,0.0005989723,0.0009690012,0.0009782189,0.2127716,0.05560252,0.1061251,0.6147737,0.000312398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005856692,0.000546157,0.793736,0.0006557826,0.0003653398,0.0004059293,0.02999722,0.1647712,0.003665711],"genre_scores_gemma":[0.0582063,0.0005394282,0.8437821,0.0005371999,0.0001007278,0.000560654,0.07616732,0.0166441,0.003462159],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01188191,"threshold_uncertainty_score":0.03948349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4593973220632835,"score_gpt":0.4301787023006636,"score_spread":0.02921861976261991,"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."}}