{"id":"W1457225595","doi":"","title":"Validating ontologies in informatics systems: approaches and lessons learned for AEC","year":2014,"lang":"en","type":"article","venue":"Journal of Information Technology in Construction","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Benchmarking; Scope (computer science); Computer science; Construct (python library); Ontology; Dimension (graph theory); Data science; Set (abstract data type); Knowledge management; Informatics; Artificial intelligence; Software engineering; Engineering; 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":[0.07566119,0.001098,0.001630459,0.008776404,0.004029335,0.01793132,0.005818541,0.006581908,0.004133104],"category_scores_gemma":[0.09942038,0.0007743879,0.001268931,0.008358363,0.02137448,0.04341599,0.008624749,0.009384461,0.001063324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01381725,"about_ca_system_score_gemma":0.01437051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02117212,"about_ca_topic_score_gemma":0.01045288,"domain_scores_codex":[0.9609853,0.02773582,0.002509331,0.001959524,0.005724585,0.001085432],"domain_scores_gemma":[0.8238802,0.1198492,0.002875013,0.02344907,0.02733847,0.002608014],"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":[0.00002589439,0.000146356,0.001720852,0.0004785903,0.00003188718,0.0001148746,0.003643082,0.005957565,0.0001987947,0.8315148,0.004630034,0.1515372],"study_design_scores_gemma":[0.00001372204,0.00002741883,0.0006023416,0.001322336,0.00001155718,0.000084027,0.004433477,0.01846597,0.0005695494,0.9347887,0.03963914,0.00004173455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02640871,0.03610369,0.7049853,0.1608438,0.0009820797,0.0007019916,0.0002629684,0.0008321368,0.0688794],"genre_scores_gemma":[0.2986248,0.01697901,0.6719751,0.00444714,0.0007207208,0.0007411169,0.0004935083,0.0003592655,0.005659337],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07566119,"threshold_uncertainty_score":0.4001394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04730560788840749,"score_gpt":0.2756129068634334,"score_spread":0.2283072989750259,"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."}}