{"id":"W36034720","doi":"10.1016/j.paid.2022.111869","title":"Assessing the quality of the requirements process","year":2011,"lang":"en","type":"dissertation","venue":"Personality and Individual Differences","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Fonds pour la Formation de Chercheurs et l'Aide à la Recherche","keywords":"Brainstorming; Checklist; Process (computing); Quality (philosophy); Waterfall model; Computer science; Process management; Set (abstract data type); Management science; Engineering management; Engineering; Software; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.011941,0.0002757572,0.0002246189,0.002807686,0.0008355933,0.003421042,0.0006701678,0.0004848026,0.002146137],"category_scores_gemma":[0.07200871,0.0002769782,0.0005770001,0.002049381,0.0009751312,0.002079516,0.001489475,0.0008374027,0.0003394255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00348014,"about_ca_system_score_gemma":0.00656768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02463433,"about_ca_topic_score_gemma":0.03658836,"domain_scores_codex":[0.9889802,0.001785768,0.0009749844,0.0003615141,0.007350822,0.0005467151],"domain_scores_gemma":[0.927268,0.02497342,0.01980622,0.005880918,0.01946753,0.002603767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002101559,0.0005582501,0.7248887,0.000491255,0.0001704061,0.0001240613,0.01372172,0.00371972,0.004460931,0.009953085,0.001530642,0.2401711],"study_design_scores_gemma":[0.00003614846,0.0007330542,0.9467769,0.0002778708,0.00007901823,0.0002446868,0.01223064,0.01110214,0.003902295,0.007412946,0.01711175,0.00009253316],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9480606,0.000373726,0.01758882,0.0003894392,0.00001866514,0.0005944287,0.0004310421,0.0001179534,0.03242527],"genre_scores_gemma":[0.9820712,0.0002044044,0.01554426,0.00002729207,0.000005406405,0.0001260341,0.0003912941,0.00001443338,0.001615571],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02463433,"threshold_uncertainty_score":0.06315082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1876503302976388,"score_gpt":0.3983763513715102,"score_spread":0.2107260210738713,"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."}}