{"id":"W39689944","doi":"10.1007/978-3-642-35758-9_50","title":"A Holistic Approach for the Architecture and Design of an Ontology-Based Data Integration Capability in Product Master Data Management","year":2012,"lang":"en","type":"book-chapter","venue":"IFIP International Federation for Information Processing/IFIP","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Ontology; Product data management; Product lifecycle; Computer science; Domain (mathematical analysis); Context (archaeology); Product management; Systems engineering; Architecture; Product (mathematics); Knowledge management; Software engineering; Process management; New product development; Engineering; Business","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":[0.002958824,0.0006722994,0.000808236,0.001664093,0.00180297,0.008516347,0.003580602,0.002309327,0.002600512],"category_scores_gemma":[0.002452691,0.001421944,0.001717947,0.003176236,0.002769311,0.009129153,0.004764653,0.003559683,0.001348802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002067883,"about_ca_system_score_gemma":0.004838854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006508872,"about_ca_topic_score_gemma":0.008403091,"domain_scores_codex":[0.9978228,0.000418898,0.000281711,0.0003630062,0.0008789674,0.000234795],"domain_scores_gemma":[0.9992792,0.0001655308,0.00005404305,0.000210805,0.0002012268,0.0000892106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003628126,0.00009787743,0.0004997124,0.000343428,0.0001036034,0.0004553224,0.002853219,0.01434275,0.009676302,0.8333825,0.009269329,0.1289396],"study_design_scores_gemma":[0.00002642627,0.00008756192,0.0006085702,0.0005065606,0.0002459677,0.0009142258,0.001224275,0.1259471,0.01315284,0.5369114,0.3202732,0.0001018871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002645833,0.0007278058,0.9854715,0.001310185,0.00009173382,0.0001107034,0.00008564438,0.0005576269,0.008999011],"genre_scores_gemma":[0.03988132,0.001358108,0.9505489,0.0004674356,0.00005484109,0.0002713424,0.0004277253,0.000218459,0.006771926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008516347,"threshold_uncertainty_score":0.01564795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1821576598778749,"score_gpt":0.3268172049720515,"score_spread":0.1446595450941766,"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."}}