{"id":"W2129544556","doi":"10.1142/s0218194002000834","title":"EVALUATING THEORIES FOR MANAGING IMPERFECT KNOWLEDGE IN HUMAN-CENTRIC DATABASE REENGINEERING ENVIRONMENTS","year":2002,"lang":"en","type":"article","venue":"International Journal of Software Engineering and Knowledge Engineering","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Documentation; Business process reengineering; Reverse engineering; Software engineering; Legacy system; Imperfect; Knowledge management; Process (computing); Data science; Systems engineering; Software; Engineering","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":[0.05293349,0.001002274,0.001135878,0.006581667,0.001650818,0.005671481,0.002704952,0.002864018,0.001528655],"category_scores_gemma":[0.2037358,0.0005548312,0.001168057,0.003174344,0.005767751,0.008251528,0.004341333,0.002350109,0.0001188723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008806279,"about_ca_system_score_gemma":0.005033164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007429515,"about_ca_topic_score_gemma":0.009762238,"domain_scores_codex":[0.9564099,0.03138457,0.001994945,0.001253098,0.007781094,0.001176456],"domain_scores_gemma":[0.542048,0.4292801,0.009277738,0.007786182,0.009681579,0.001926289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003106295,0.002368218,0.02983077,0.001501704,0.0007087444,0.0006276155,0.003407522,0.6723829,0.00178289,0.140364,0.001319465,0.1425999],"study_design_scores_gemma":[0.0003310724,0.001277489,0.003932117,0.0002092226,0.0003465654,0.0001045888,0.002646038,0.9099668,0.003482991,0.07676036,0.0008703999,0.00007237057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7855766,0.0008535509,0.1976927,0.0027159,0.00004049969,0.001400286,0.0002443464,0.0003112204,0.01116487],"genre_scores_gemma":[0.8986441,0.0003626322,0.09971368,0.000169319,0.00002721913,0.00053656,0.0002311105,0.00001963038,0.0002956267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05293349,"threshold_uncertainty_score":0.2799424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763679813323434,"score_gpt":0.2950097237874491,"score_spread":0.2673729256542147,"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."}}