{"id":"W2159217028","doi":"10.1109/icsmc.1997.626217","title":"Defining quality and reliability: a linear graph model perspective","year":2002,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reliability (semiconductor); Computer science; Quality (philosophy); Perspective (graphical); Graph; Reliability theory; Software quality; Reliability engineering; Graph theory; Theoretical computer science; Mathematics; Artificial intelligence; Engineering; Epistemology; Failure rate; 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":[0.0001895743,0.00009683034,0.0001271618,0.00003974464,0.00004843406,0.00001816839,0.00004296083,0.00006673525,0.00006878544],"category_scores_gemma":[0.0001736335,0.00008844873,0.00003819727,0.0001227094,0.00005514707,0.0001666332,0.00001725695,0.000113357,0.0000191406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005806944,"about_ca_system_score_gemma":0.000003190665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005160603,"about_ca_topic_score_gemma":0.00001040813,"domain_scores_codex":[0.9993938,0.00001743054,0.0001675262,0.0001864449,0.00008100788,0.0001538103],"domain_scores_gemma":[0.9996167,0.00004984737,0.00001314868,0.000186298,0.00007906312,0.00005490072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003712224,0.00002114839,0.0002824428,0.00003459589,0.000007302167,2.790185e-7,0.001031994,0.94448,0.00004801179,0.05294437,0.0005166694,0.0006294755],"study_design_scores_gemma":[0.0001584884,0.00001293105,0.0002542763,0.000007094612,0.000005669225,0.000001284091,0.0003620713,0.9824153,0.00008944429,0.01648098,0.00009056397,0.0001219532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1563244,0.001011836,0.6793191,0.001304919,0.0001262632,0.0002992444,0.00001306278,0.0009681811,0.160633],"genre_scores_gemma":[0.9441175,0.0005739948,0.05475927,0.0001141226,0.00001272177,0.00001302426,0.000001733366,0.00001633326,0.0003913256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7877931,"threshold_uncertainty_score":0.3606834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021219434849232,"score_gpt":0.247941631783188,"score_spread":0.2277294374346956,"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."}}