{"id":"W1533768523","doi":"10.1109/wcre.1996.558889","title":"Reverse engineering a medical database","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Reverse engineering; Variety (cybernetics); Relational database; Database; Database design; Data science; Software engineering; Artificial intelligence","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":[0.009078231,0.0006245313,0.0007668191,0.003120894,0.001139564,0.004113794,0.00237515,0.001433827,0.003505502],"category_scores_gemma":[0.02920095,0.0008732837,0.001591424,0.002588138,0.001355497,0.005186449,0.003421328,0.00327398,0.001944577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454577,"about_ca_system_score_gemma":0.003987353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003092211,"about_ca_topic_score_gemma":0.003757646,"domain_scores_codex":[0.9932683,0.002160603,0.0005005493,0.0006814887,0.003190758,0.0001983713],"domain_scores_gemma":[0.9730521,0.01066309,0.001127688,0.01022307,0.004636351,0.0002976854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002575342,0.0002764999,0.004596494,0.001072365,0.0001790741,0.002666308,0.001524181,0.02442994,0.02443991,0.1539853,0.02084411,0.7657282],"study_design_scores_gemma":[0.0001207205,0.000543322,0.001593993,0.0008852507,0.0003821587,0.01306666,0.001352366,0.1904835,0.07475552,0.1453651,0.5712732,0.0001781919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01339886,0.001604978,0.972326,0.003400966,0.000393516,0.0004016431,0.0006612935,0.00229839,0.005514453],"genre_scores_gemma":[0.07236306,0.002111373,0.9170039,0.001559902,0.0001294839,0.0001618002,0.001590928,0.0002988011,0.004780644],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009078231,"threshold_uncertainty_score":0.04801089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01612089944636406,"score_gpt":0.214473635856314,"score_spread":0.1983527364099499,"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."}}