{"id":"W2078869985","doi":"10.1115/detc2011-48139","title":"Grammatical and Semantic Disambiguation of Requirements at Elicitation and Representation Stages","year":2011,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Natural language processing; Semantics (computer science); Requirements elicitation; Context (archaeology); Representation (politics); Process (computing); Ambiguity; Natural language; Selection (genetic algorithm); Artificial intelligence; Grammar; Natural language generation; Requirements engineering; Linguistics; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02760229,0.001026209,0.0006952944,0.002100152,0.001255137,0.00366503,0.001248129,0.001463798,0.004681618],"category_scores_gemma":[0.07326631,0.0009600816,0.001457639,0.001442419,0.004040489,0.004296529,0.003424673,0.001802074,0.001605454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001975532,"about_ca_system_score_gemma":0.003444915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007617711,"about_ca_topic_score_gemma":0.0007243338,"domain_scores_codex":[0.936162,0.04944379,0.003003633,0.002437375,0.007894212,0.001059026],"domain_scores_gemma":[0.9316269,0.04973737,0.003185431,0.01018574,0.004869614,0.0003949851],"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":[0.001351621,0.0007585193,0.007605969,0.002197838,0.0001302813,0.001079545,0.05127085,0.025299,0.126617,0.4259898,0.003505542,0.354194],"study_design_scores_gemma":[0.0004347105,0.001233773,0.01313141,0.0009486387,0.0003042259,0.001491522,0.02050954,0.08111196,0.362573,0.3984435,0.1192771,0.0005406242],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1324857,0.0002607359,0.8418576,0.0008825059,0.00008926366,0.001837279,0.0002670869,0.0008738534,0.02144598],"genre_scores_gemma":[0.5363047,0.0002344381,0.4581043,0.0002478074,0.00002964937,0.001623835,0.0004255098,0.0003516992,0.002678082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02760229,"threshold_uncertainty_score":0.1459767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09441219050162285,"score_gpt":0.3142650474198199,"score_spread":0.2198528569181971,"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."}}