{"id":"W2179916386","doi":"10.1007/978-3-540-89778-1_1","title":"Ambiguity in Natural Language Requirements Documents","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ambiguity; Natural (archaeology); Computer science; Linguistics; Natural language; Natural language processing; Programming language; History; Philosophy; Archaeology","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":[0.005636769,0.000821854,0.001119597,0.003310174,0.001910237,0.005762046,0.001493978,0.001817807,0.006054046],"category_scores_gemma":[0.0314485,0.001819484,0.001182889,0.003396703,0.002777276,0.01294124,0.00308571,0.003751486,0.002406271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001927866,"about_ca_system_score_gemma":0.002100476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001628046,"about_ca_topic_score_gemma":0.001222904,"domain_scores_codex":[0.9882882,0.004182887,0.001309008,0.0009578491,0.004731839,0.0005301675],"domain_scores_gemma":[0.9767973,0.01712197,0.00118365,0.00230559,0.002338831,0.0002526322],"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":[0.0001378815,0.00006777481,0.0007655676,0.0005371257,0.00002118927,0.0009395248,0.003981256,0.008285034,0.004411249,0.7896033,0.0103992,0.1808509],"study_design_scores_gemma":[0.00002830027,0.00004186607,0.0003805687,0.0003396309,0.00002867977,0.001279213,0.001222512,0.02642585,0.009165588,0.8764579,0.08455548,0.00007443409],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02566673,0.002888706,0.9048654,0.002314102,0.0003104845,0.0002852371,0.00055319,0.001626907,0.06148921],"genre_scores_gemma":[0.498154,0.002894182,0.462014,0.0008081254,0.0004424506,0.000380117,0.002597705,0.001702142,0.03100717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006054046,"threshold_uncertainty_score":0.02981043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.015582989552096,"score_gpt":0.2882899828273541,"score_spread":0.272706993275258,"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."}}