{"id":"W2204842813","doi":"10.1109/sita.2015.7358442","title":"Schema Matching as complex adaptive system","year":2015,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Schema matching; Computer science; Schema (genetic algorithms); Schema evolution; Matching (statistics); Complex system; Complex adaptive system; Data science; Artificial intelligence; Data mining; Theoretical computer science; Machine learning; Database schema; Data integration; Mathematics","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":[0.00362123,0.0003786854,0.0007006524,0.001850665,0.001170841,0.004645028,0.002037311,0.001850821,0.004219996],"category_scores_gemma":[0.01033449,0.000498299,0.00106532,0.002346016,0.003228225,0.006897816,0.004030111,0.001791625,0.0006638805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970116,"about_ca_system_score_gemma":0.001549454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002886282,"about_ca_topic_score_gemma":0.00140334,"domain_scores_codex":[0.9968081,0.001092026,0.0002641219,0.000972439,0.0007160548,0.0001471709],"domain_scores_gemma":[0.9956931,0.002071603,0.0005046362,0.001048987,0.0004229647,0.000258689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006844211,0.00007178789,0.002631847,0.0002427146,0.0001496576,0.000317788,0.001126406,0.08921567,0.003469774,0.8143679,0.002182228,0.08615597],"study_design_scores_gemma":[0.00002268631,0.00003098782,0.0006013522,0.00004720024,0.00004927051,0.0003067969,0.000259184,0.3346834,0.001658408,0.6411054,0.0211974,0.00003786394],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02321808,0.000936824,0.9650396,0.001609114,0.00006545895,0.0001611621,0.0001068821,0.000718197,0.008144665],"genre_scores_gemma":[0.419526,0.001310557,0.5721548,0.0006059669,0.00008803542,0.000290524,0.0004306427,0.0001630918,0.005430356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004645028,"threshold_uncertainty_score":0.01915115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1023216497059875,"score_gpt":0.2867629401899376,"score_spread":0.1844412904839501,"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."}}