{"id":"W2043640532","doi":"10.1016/j.datak.2004.12.009","title":"Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties","year":2005,"lang":"en","type":"article","venue":"Data & Knowledge Engineering","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":239,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CLARITY; Computer science; Grammar; Cognitive psychology; Natural language processing; Rule-based machine translation; Domain (mathematical analysis); Domain model; Linguistics; Psychology; Artificial intelligence; Domain knowledge; Mathematics","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":[0.03382764,0.0006411945,0.001116196,0.005034317,0.001970216,0.008770312,0.002337766,0.002362881,0.00347339],"category_scores_gemma":[0.1901595,0.001270463,0.0028839,0.002848749,0.006286419,0.03101921,0.005235642,0.00314922,0.0003575285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002785674,"about_ca_system_score_gemma":0.002726292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001938796,"about_ca_topic_score_gemma":0.001848945,"domain_scores_codex":[0.9672541,0.01738322,0.002984583,0.001404837,0.009811774,0.001161466],"domain_scores_gemma":[0.6466206,0.2916571,0.01680204,0.02600557,0.01604778,0.002866827],"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":[0.0008382776,0.0001710676,0.01718072,0.0007463022,0.0002386593,0.0002174487,0.006827567,0.0227567,0.003650745,0.8801969,0.001837136,0.06533858],"study_design_scores_gemma":[0.0001074884,0.0002214628,0.008904579,0.0004259837,0.0003629747,0.0003620112,0.00187039,0.1559051,0.005998082,0.8202013,0.005505945,0.0001347647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2797855,0.001792548,0.691824,0.003411695,0.0001592336,0.0003002284,0.0005127535,0.0005448741,0.02166927],"genre_scores_gemma":[0.9130039,0.0005467187,0.08490016,0.0001376297,0.00009648815,0.0001423402,0.000444105,0.0001891162,0.0005396481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03382764,"threshold_uncertainty_score":0.1788998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2068040600089384,"score_gpt":0.3213727864468606,"score_spread":0.1145687264379222,"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."}}