{"id":"W1762375712","doi":"10.3968/4845","title":"The Software Reliability Increase Method","year":2014,"lang":"en","type":"article","venue":"Studies in sociology of science","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reliability engineering; Code refactoring; Reliability (semiconductor); Computer science; Statistic; Software quality; Software reliability testing; Software; Software metric; Process (computing); Probabilistic logic; Statistics; Software development; Programming language; Mathematics; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00293816,0.0009044291,0.0006373203,0.004217624,0.0005333783,0.001551925,0.001347204,0.0007496268,0.005652909],"category_scores_gemma":[0.01119958,0.0004198145,0.0009861176,0.001968086,0.0008797177,0.002377205,0.001750353,0.001585491,0.002226276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007771701,"about_ca_system_score_gemma":0.001369386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007121256,"about_ca_topic_score_gemma":0.0006869566,"domain_scores_codex":[0.9948237,0.001291167,0.0002014705,0.001108146,0.002403338,0.0001720831],"domain_scores_gemma":[0.9914066,0.00372403,0.0009111179,0.00132996,0.00241838,0.0002099346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001630632,0.0001998951,0.009618636,0.0007448398,0.00007724797,0.0001999994,0.0005712045,0.01176106,0.0127442,0.06661958,0.007951507,0.8893487],"study_design_scores_gemma":[0.0002921074,0.002039526,0.03914031,0.0008178568,0.0005652252,0.005256765,0.0009225223,0.498409,0.05867971,0.1500169,0.2434787,0.0003813317],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0164911,0.0009313015,0.957652,0.0005163713,0.0001703124,0.0004751685,0.0003459512,0.003554162,0.0198637],"genre_scores_gemma":[0.2063957,0.0007779867,0.780409,0.000209229,0.0002904563,0.00089894,0.0004406594,0.0004288947,0.01014913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9994666,"threshold_uncertainty_score":0.01891083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03808919645315161,"score_gpt":0.3876887638517571,"score_spread":0.3495995673986055,"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."}}