{"id":"W2172460036","doi":"","title":"Requirements for Tools for Ambiguity Identification and Measurement in Natural Language Requirements Specifications.","year":2007,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ambiguity; RSS; Computer science; Natural language; Identification (biology); Set (abstract data type); Sentence; Software requirements specification; Natural (archaeology); Natural language processing; Artificial intelligence; Programming language; Software; World Wide Web; Software development","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":[0.001824462,0.0001453979,0.0001413086,0.0001940456,0.0001507303,0.0002503065,0.0005666135,0.00004973228,0.000003321314],"category_scores_gemma":[0.00007417673,0.0001320684,0.00005067463,0.0003334541,0.00001880676,0.0008565895,0.0001119076,0.00006490406,0.000004497776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001177253,"about_ca_system_score_gemma":0.00003091535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009917122,"about_ca_topic_score_gemma":0.001476481,"domain_scores_codex":[0.9982419,0.0000257884,0.0004659007,0.0005014618,0.0004050436,0.0003598827],"domain_scores_gemma":[0.9988947,0.0001420788,0.000145438,0.0004859247,0.0002580054,0.00007386949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001987147,0.0003958297,0.002439423,0.0003284285,0.00007989223,0.000003428097,0.007049243,0.00001396891,0.2400964,0.08763324,0.0005702385,0.6611912],"study_design_scores_gemma":[0.00935716,0.0005135869,0.3860275,0.0003088469,0.00008342818,0.00001378908,0.00523615,0.0377642,0.4965877,0.02553883,0.03692233,0.001646457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1089966,0.0004598755,0.8859704,0.001438755,0.0005892522,0.001564587,0.000008997303,0.0001141372,0.0008574476],"genre_scores_gemma":[0.9583444,0.000008536061,0.04045058,0.0007990027,0.0000840151,0.0001270307,0.00003846135,0.000009752734,0.0001382196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8493478,"threshold_uncertainty_score":0.5385593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09301943506624619,"score_gpt":0.3227899777346964,"score_spread":0.2297705426684502,"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."}}