{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00316997,0.000181153,0.0003196267,0.001367147,0.0009890521,0.0002103116,0.0009731468,0.0001149847,0.000002965926],"category_scores_gemma":[0.0009564086,0.0001823646,0.0002141695,0.003048967,0.0002074166,0.006094282,0.0005279051,0.0002506582,0.00004971262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002015217,"about_ca_system_score_gemma":0.0006070856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009042839,"about_ca_topic_score_gemma":0.00001209094,"domain_scores_codex":[0.9972147,0.0002277409,0.0004052736,0.0003522932,0.001270224,0.000529753],"domain_scores_gemma":[0.997027,0.0008680588,0.0001330747,0.0004813715,0.001306956,0.0001835107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002373403,0.00002489235,0.0001426667,0.00006178823,0.0001570447,0.000003422846,0.0008136286,0.540952,0.000003934017,0.4557369,0.00001558801,0.002064403],"study_design_scores_gemma":[0.004472958,0.0004028596,0.02062047,0.0001603905,0.0001534658,0.00003659424,0.005335918,0.930137,0.0002103967,0.03355017,0.004091576,0.0008281636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008046966,0.00002626579,0.9872337,0.0002117324,0.0003270079,0.0005813997,0.00005957901,0.000451478,0.003061879],"genre_scores_gemma":[0.8500132,0.000004731708,0.1497647,0.00001291133,0.00003837167,0.00007327742,0.00005183476,0.000003586084,0.00003737811],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8419662,"threshold_uncertainty_score":0.7607089,"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."}}