{"id":"W4395098143","doi":"10.1007/978-981-97-2266-2_10","title":"Graph Neural Network Approach to Semantic Type Detection in Tables","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Table (database); Graph; Security token; Artificial intelligence; Focus (optics); Key (lock); Artificial neural network; Data mining; Natural language processing; Machine learning; Theoretical computer science","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":[0.0003992171,0.0004167538,0.000558258,0.002574914,0.0005298869,0.00174649,0.001387698,0.0007249017,0.008599093],"category_scores_gemma":[0.002487364,0.0003850055,0.0009107405,0.002701734,0.0003610515,0.002756302,0.0006252364,0.0007802745,0.002001516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145637,"about_ca_system_score_gemma":0.000750516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01312063,"about_ca_topic_score_gemma":0.01999964,"domain_scores_codex":[0.9996653,0.00004569914,0.00002362572,0.0001131223,0.0001161837,0.00003619277],"domain_scores_gemma":[0.9992934,0.0003047223,0.00005094723,0.0001094975,0.0002145464,0.000026813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003703031,0.0001445456,0.005296677,0.0003929155,0.0001229635,0.0002801169,0.000176769,0.1394917,0.01071164,0.09781171,0.03427416,0.7109265],"study_design_scores_gemma":[0.000007721683,0.00002104499,0.0009538425,0.00004703824,0.00004831325,0.0001060048,0.00007644846,0.8968034,0.006421697,0.08408616,0.01141134,0.00001700502],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02414558,0.0008778765,0.953221,0.0005482698,0.0002481921,0.0001204439,0.004358427,0.005383043,0.01109715],"genre_scores_gemma":[0.3180864,0.0009243134,0.6528161,0.0002204352,0.0001299075,0.00009927909,0.00688129,0.0006265002,0.0202158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01312063,"threshold_uncertainty_score":0.02876687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01549184687362823,"score_gpt":0.2358622625470314,"score_spread":0.2203704156734032,"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."}}