{"id":"W2139787745","doi":"10.1109/noms.2012.6212000","title":"A hybrid approach to operating system discovery based on diagnosis theory","year":2012,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Formalism (music); Extension (predicate logic); Theoretical computer science; Machine learning; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001473139,0.000159126,0.0001938659,0.00008752578,0.0001807345,0.000222728,0.0005897947,0.00003829781,0.000005910459],"category_scores_gemma":[0.00009368214,0.000102702,0.00008398819,0.0002364084,0.00001689302,0.0009483918,0.000166604,0.00009309527,0.0002291415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001217201,"about_ca_system_score_gemma":0.00004512721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002886264,"about_ca_topic_score_gemma":1.973984e-7,"domain_scores_codex":[0.9984906,0.000189367,0.0002416843,0.0003607206,0.0003181322,0.0003994937],"domain_scores_gemma":[0.9985936,0.000304495,0.00004184267,0.0008471113,0.0000404903,0.0001725179],"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":[0.00005132099,0.002086179,0.3535084,0.0012505,0.00006879403,0.000007854872,0.00387687,0.02367994,0.000113695,0.5572956,0.009515782,0.04854516],"study_design_scores_gemma":[0.001369286,0.0006360273,0.05811767,0.0008550362,0.0000359049,0.00008329406,0.00141236,0.9045171,0.02648854,0.0002071667,0.004441351,0.001836241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1269154,0.00003933999,0.8476514,0.0001171681,0.0006921185,0.0004036452,0.000002414904,0.0003776673,0.02380084],"genre_scores_gemma":[0.9704378,4.932648e-7,0.02789161,0.0009454068,0.0001898078,0.0002965197,0.000001686022,0.000009749516,0.0002269312],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8808372,"threshold_uncertainty_score":0.4188067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0138947505724015,"score_gpt":0.2274593882845085,"score_spread":0.213564637712107,"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."}}