{"id":"W62849181","doi":"10.5555/1929757.1929784","title":"Contextual factors in database integration: a Delphi study","year":2010,"lang":"en","type":"article","venue":"International Conference on Conceptual Modeling","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Schema matching; Heuristics; Computer science; Data integration; Database schema; Schema migration; Matching (statistics); Schema (genetic algorithms); Conceptual schema; Database; Delphi method; Delphi; Information integration; Information retrieval; Knowledge management; Data mining; Data science; Database design; Artificial intelligence; Semi-structured model","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":[0.06564808,0.0005433583,0.0007572226,0.003171154,0.009330191,0.00660783,0.001423207,0.001873345,0.003135645],"category_scores_gemma":[0.09911046,0.001124972,0.0006900787,0.003919641,0.003506323,0.006575765,0.007202487,0.002221719,0.0003066062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00605716,"about_ca_system_score_gemma":0.01042419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009499149,"about_ca_topic_score_gemma":0.01325785,"domain_scores_codex":[0.9357468,0.05054433,0.003164168,0.001545583,0.004679519,0.004319567],"domain_scores_gemma":[0.8551702,0.1225383,0.003309583,0.002202299,0.01400418,0.002775489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009568114,0.00128644,0.09535366,0.0009991464,0.000121488,0.001146848,0.8207468,0.0009606941,0.002024919,0.008949151,0.0009141497,0.0665399],"study_design_scores_gemma":[0.00004107441,0.0004599863,0.02556703,0.0004718238,0.000107103,0.0002708332,0.9651425,0.001508427,0.001064536,0.001552547,0.003765363,0.00004875721],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870999,0.0002199175,0.005116527,0.0007247241,0.00001488888,0.0006302836,0.00003544775,0.000007813655,0.00615046],"genre_scores_gemma":[0.9959612,0.0002187053,0.002819643,0.0001975468,0.000004557413,0.00032291,0.00002269814,0.00000893487,0.0004438183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06564808,"threshold_uncertainty_score":0.3471844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1534381364262396,"score_gpt":0.3499412891156573,"score_spread":0.1965031526894177,"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."}}