{"id":"W2139608538","doi":"10.1007/s00766-005-0008-3","title":"Applying a pragmatics-based creativity-fostering technique to requirements elicitation","year":2005,"lang":"en","type":"article","venue":"Requirements Engineering","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Brainstorming; Requirements elicitation; Pragmatics; Viewpoints; Creativity; Computer science; Requirements engineering; Process (computing); Artificial intelligence; Software engineering; Human–computer interaction; Psychology; Linguistics; Programming language; Software; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008095359,0.000310476,0.0002435616,0.0004491622,0.0001164645,0.0002690081,0.0007733623,0.00009127858,0.0000142412],"category_scores_gemma":[0.0003106502,0.0003466304,0.00007286355,0.0006591757,0.000005780007,0.001795867,0.0003847934,0.000203574,0.00004463688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003095702,"about_ca_system_score_gemma":0.00003862493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001295618,"about_ca_topic_score_gemma":0.000001629694,"domain_scores_codex":[0.9980122,0.00003605009,0.0004546521,0.0004710352,0.0005101626,0.0005158416],"domain_scores_gemma":[0.9987051,0.0001898947,0.0001316751,0.0007076345,0.0000790727,0.0001866328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002130153,0.000232173,0.0004044388,0.0004327706,0.0001088714,0.00003111473,0.0008597394,0.2994587,0.3745672,0.0115248,0.0004780282,0.3118808],"study_design_scores_gemma":[0.0005496156,0.0002591336,0.0004270876,0.0007717892,0.00002602154,0.00002239639,0.00001059015,0.7173797,0.1937546,0.0003079384,0.08548844,0.001002695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004051811,0.0000558949,0.9915112,0.0004044788,0.0002208417,0.001273857,0.000001604397,0.001876447,0.0006038839],"genre_scores_gemma":[0.4195078,0.000004274981,0.5790678,0.000225079,0.00008633096,0.001050864,0.000002760159,0.00003440667,0.00002069135],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.417921,"threshold_uncertainty_score":0.9998986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04752296869247587,"score_gpt":0.3201825230249677,"score_spread":0.2726595543324919,"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."}}