{"id":"W4386158789","doi":"10.1109/csci58124.2022.00339","title":"Improving Quality of Software Requirements by Using a Triplet Structure","year":2022,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Software requirements specification; Software requirements; Software engineering; Requirements analysis; Software construction; Software development; Requirement; Verification and validation; Software system; Software quality; Requirements engineering; Software; Programming language; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004976612,0.0005522933,0.0009084079,0.00376953,0.001610049,0.002535872,0.001180605,0.001348407,0.004794653],"category_scores_gemma":[0.02029747,0.0006588284,0.001661499,0.003973806,0.001809715,0.005365115,0.002075433,0.002353896,0.001486638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001558672,"about_ca_system_score_gemma":0.002559029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002641483,"about_ca_topic_score_gemma":0.003656463,"domain_scores_codex":[0.9930362,0.002279972,0.0008446938,0.0009413823,0.002639877,0.0002579581],"domain_scores_gemma":[0.9842278,0.006677188,0.001647926,0.003967128,0.003161902,0.0003181085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000402033,0.0004606417,0.005219752,0.0007997965,0.00009066966,0.001381521,0.004396625,0.0438525,0.03720116,0.5006883,0.01175367,0.3937533],"study_design_scores_gemma":[0.0001891384,0.0006645853,0.002267838,0.0004126793,0.0001488282,0.001266655,0.0008266481,0.44691,0.04140943,0.3963277,0.1094214,0.0001552293],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01513118,0.00008131791,0.9751789,0.0004283531,0.00008103165,0.0002336376,0.0003478759,0.002115466,0.006402226],"genre_scores_gemma":[0.09050805,0.0001342177,0.9054201,0.0001173438,0.00003557089,0.0002743474,0.000767447,0.0005522784,0.002190671],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004976612,"threshold_uncertainty_score":0.02631915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487905860566675,"score_gpt":0.323466724958686,"score_spread":0.2746761389020185,"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."}}