{"id":"W3137652218","doi":"10.33915/etd.1146","title":"Software tool for reliability estimation","year":2001,"lang":"en","type":"dissertation","venue":"","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Software construction; Software reliability testing; Computer science; Software sizing; Software; Avionics software; Reliability (semiconductor); Reliability engineering; Software quality; Verification and validation; Software system; Component (thermodynamics); Component-based software engineering; Software development; Embedded system; Software engineering; Engineering; Operating system; Power (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001940334,0.00192353,0.001397329,0.003087798,0.0005552833,0.001413835,0.002820917,0.001078777,0.04494552],"category_scores_gemma":[0.01106065,0.001089622,0.001444274,0.002258026,0.0003562144,0.00233504,0.001481102,0.002414645,0.0261977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004519422,"about_ca_system_score_gemma":0.001167024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001072527,"about_ca_topic_score_gemma":0.000909738,"domain_scores_codex":[0.9978681,0.0003607241,0.0002234544,0.0002687187,0.001153267,0.0001257612],"domain_scores_gemma":[0.9941552,0.002800232,0.0002658052,0.0008536117,0.001822718,0.0001024539],"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":[0.0003899942,0.0002131974,0.001579116,0.001378501,0.00019678,0.0004013416,0.0003146323,0.0330766,0.02169329,0.03708233,0.1984977,0.7051766],"study_design_scores_gemma":[0.0003879456,0.0003022523,0.002452632,0.0005663562,0.000230206,0.001570734,0.0001068366,0.35977,0.04334681,0.04819092,0.5428495,0.0002258377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001174535,0.0002896835,0.9228587,0.00007155768,0.0001200508,0.0002026405,0.002045537,0.06777183,0.00546555],"genre_scores_gemma":[0.03164948,0.000799693,0.9276417,0.0001670208,0.0001176465,0.001287533,0.01064585,0.01193129,0.01575978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04494552,"threshold_uncertainty_score":0.1503577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595859706374152,"score_gpt":0.3189155740456106,"score_spread":0.302956976981869,"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."}}