{"id":"W2087347311","doi":"10.1145/1137702.1137717","title":"Exploring robust component-based software","year":2006,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Component-based software engineering; Software construction; Software sizing; Component (thermodynamics); Robustness (evolution); Software system; Software development; Software; Software engineering; Reliability engineering; Software design; Systems engineering; Engineering; Operating system","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":[0.0002198824,0.0001194096,0.000135268,0.00007781851,0.0001424979,0.00009561616,0.0005209547,0.00003605707,0.00002662465],"category_scores_gemma":[0.0000151212,0.00009272999,0.00007612131,0.0002965477,0.00002952956,0.0007159652,0.00009694842,0.00007768872,0.0002230174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005036325,"about_ca_system_score_gemma":0.0000475737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003597201,"about_ca_topic_score_gemma":0.00001959608,"domain_scores_codex":[0.9988955,0.00003015372,0.000230097,0.0003161043,0.0002601176,0.0002680318],"domain_scores_gemma":[0.9991387,0.00008836422,0.00004527453,0.0006047393,0.00006921939,0.00005372758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003220272,0.001060036,0.5914187,0.0005332946,0.00003957375,0.00008960244,0.0004243111,0.2032762,0.001179596,0.04177193,0.02019711,0.1399774],"study_design_scores_gemma":[0.002642554,0.000244796,0.5403791,0.0002174109,0.00001580111,0.00004156599,0.00007802273,0.3809152,0.03422064,0.002426805,0.03715717,0.001660877],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1724038,0.00003661075,0.82433,0.0003012607,0.0005695394,0.0001071081,6.052254e-7,0.0009234286,0.0013277],"genre_scores_gemma":[0.8536035,0.000001622877,0.1458796,0.000154354,0.000110064,0.00003984808,0.000003922891,0.000007107754,0.0001999365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6811997,"threshold_uncertainty_score":0.3781419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06775398232971076,"score_gpt":0.2187782178387219,"score_spread":0.1510242355090112,"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."}}