{"id":"W185646288","doi":"","title":"Anisotropic Laplace trend to enhance software reliability growth modelling","year":2007,"lang":"en","type":"article","venue":"","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Concordia University","funders":"","keywords":"Laplace transform; Reliability engineering; Reliability (semiconductor); Computer science; Software quality; Software; Statistic; Mathematical optimization; Software development; Mathematics; Engineering; Statistics; Mathematical analysis; Physics","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":[0.001666706,0.0001877095,0.0002616776,0.0002310435,0.0002125429,0.0001814601,0.001275362,0.0001020266,0.00008055372],"category_scores_gemma":[0.0005797849,0.0001622648,0.0001516164,0.001578035,0.00006001909,0.0004915504,0.0004474339,0.0002539329,0.0002712468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001587308,"about_ca_system_score_gemma":0.00007891328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003623591,"about_ca_topic_score_gemma":0.0001939098,"domain_scores_codex":[0.997206,0.00009193583,0.0004124151,0.0008807884,0.0007137525,0.0006951392],"domain_scores_gemma":[0.9974673,0.0007392521,0.00004665682,0.001096643,0.0002646305,0.0003854855],"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":[0.0003240449,0.002242179,0.1074215,0.0005298952,0.0002163681,0.0002120907,0.006112458,0.1550865,0.003197354,0.1321359,0.01153773,0.580984],"study_design_scores_gemma":[0.001013172,0.001123092,0.01471799,0.0001544391,0.00004721467,0.0000316193,0.0003201125,0.706091,0.1346894,0.09981166,0.03927358,0.002726738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09183045,0.00005542772,0.9048799,0.001304349,0.00009449135,0.0001588295,0.000001574022,0.0004510832,0.001223862],"genre_scores_gemma":[0.6127051,0.00002059783,0.385593,0.000389853,0.00005629628,0.000008673322,0.000001749609,0.000008726423,0.001216073],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5782573,"threshold_uncertainty_score":0.6616967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01624363542795891,"score_gpt":0.2988234154306988,"score_spread":0.2825797800027399,"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."}}