{"id":"W1605491627","doi":"10.1109/re.2004.56","title":"Visual variability analysis for goal models","year":2004,"lang":"en","type":"article","venue":"Institutional Research Information System (Università degli Studi di Trento)","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Abstraction; Goal modeling; Goal orientation; Contrast (vision); Qualitative analysis; Visualization; Quantitative analysis (chemistry); Risk analysis (engineering); Requirements engineering; Management science; Artificial intelligence; Engineering; Software; Qualitative research; Programming language","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":[0.003506863,0.001002785,0.0005168957,0.002745863,0.0007659565,0.003037575,0.00118927,0.001122082,0.006468097],"category_scores_gemma":[0.01385894,0.0005775209,0.001800032,0.001028521,0.001310983,0.003195281,0.002762078,0.001858239,0.001025055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00139924,"about_ca_system_score_gemma":0.001214692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002524904,"about_ca_topic_score_gemma":0.001876907,"domain_scores_codex":[0.9978849,0.0008304108,0.0001339838,0.0002684117,0.0007703261,0.0001119577],"domain_scores_gemma":[0.9924653,0.00497849,0.0005608634,0.001059302,0.0007968534,0.0001392339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004085689,0.0001217064,0.002068672,0.0005716225,0.0001198332,0.0004621064,0.003119017,0.1614546,0.0261226,0.5049291,0.0118689,0.2887534],"study_design_scores_gemma":[0.00005918014,0.00005707267,0.0006880088,0.0001974652,0.0000448882,0.0001891627,0.0003971134,0.5764354,0.01150482,0.3784404,0.03191636,0.00007001965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002545091,0.00004489277,0.9935556,0.0001190144,0.00001131769,0.00004286371,0.0001090959,0.001716856,0.001855245],"genre_scores_gemma":[0.1715707,0.0001592049,0.8244898,0.0001170527,0.00002686147,0.0004389897,0.0005951219,0.0009106115,0.001691642],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006468097,"threshold_uncertainty_score":0.02163792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1279975732181197,"score_gpt":0.3688569832145502,"score_spread":0.2408594099964305,"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."}}