{"id":"W2056331670","doi":"10.1007/s11155-006-9020-7","title":"Requirements Analysis for Engineering Computation: A Systematic Approach for Improving Reliability","year":2006,"lang":"en","type":"article","venue":"Reliable Computing","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Documentation; Computer science; Software requirements specification; Software engineering; Requirements engineering; System requirements specification; Requirements analysis; Reliability (semiconductor); Computation; Reliability engineering; Functional specification; Argument (complex analysis); Software; Software system; Systems engineering; Programming language; Software construction; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003632932,0.0002840757,0.0008128477,0.0004952922,0.0004878527,0.0005091591,0.0009254255,0.0001229062,0.000001016867],"category_scores_gemma":[0.0009416571,0.0002717338,0.0006399002,0.002273424,0.00003302353,0.0003817797,0.000301343,0.0001587182,0.000002881497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878961,"about_ca_system_score_gemma":0.0001053257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001692691,"about_ca_topic_score_gemma":0.000002080231,"domain_scores_codex":[0.9965017,0.0001008745,0.001043402,0.001018497,0.0005771489,0.0007583266],"domain_scores_gemma":[0.9963966,0.001610435,0.0003507014,0.0008346324,0.00069084,0.0001168041],"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":[0.000007367206,0.0001506198,0.002940253,0.0124907,0.0002398423,7.001291e-7,0.00007309271,0.979371,0.0001867402,0.003525182,0.0000912617,0.0009232976],"study_design_scores_gemma":[0.0004732871,0.00005034989,0.0005259131,0.0001877184,0.0002921459,0.000002155908,0.00002384658,0.9968919,0.0002150987,0.001005975,0.00004088098,0.000290785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007064924,0.0002952947,0.9901294,0.00008725932,0.0001434843,0.001737995,0.000006336068,0.0004449876,0.00009033264],"genre_scores_gemma":[0.532809,7.096332e-7,0.4668128,0.00001495038,0.0001056538,0.000146735,0.00004642336,0.00001545406,0.00004827193],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5257441,"threshold_uncertainty_score":0.9999735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02422770441222972,"score_gpt":0.278808969988708,"score_spread":0.2545812655764783,"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."}}