{"id":"W4248290991","doi":"10.1007/978-3-642-16373-9_5","title":"Finding Solutions in Goal Models: An Interactive Backward Reasoning Approach","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Viewpoints; Computer science; Ask price; Human–computer interaction; Domain (mathematical analysis); Goal orientation; Management science","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001980975,0.0006124942,0.0006498971,0.001333026,0.0002858463,0.0004398008,0.003855876,0.0005274706,0.000003845863],"category_scores_gemma":[0.0006852086,0.0006129399,0.0001142452,0.0007936495,0.0006064069,0.002443375,0.002025584,0.002709771,0.000008027931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005759926,"about_ca_system_score_gemma":0.0004278724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003047373,"about_ca_topic_score_gemma":0.00008818573,"domain_scores_codex":[0.9957434,0.0001065794,0.0005335094,0.001918922,0.0007036642,0.0009939297],"domain_scores_gemma":[0.9963833,0.001403312,0.0002558651,0.001591525,0.000179394,0.000186568],"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":[0.000004326776,0.00002426211,0.000008822612,0.00001552541,0.000004641598,0.00003417732,0.00186646,0.8065178,0.0001872794,0.02076743,7.343315e-7,0.1705686],"study_design_scores_gemma":[0.0001401107,0.00006766007,0.0000548347,0.0002279042,0.000002799126,0.00006958908,0.000001007576,0.7197626,0.0003183083,0.2787797,0.00004769412,0.0005278676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001148288,0.0002269608,0.9952903,0.00009163767,0.001965729,0.000350456,0.000004350963,0.0004652277,0.001490452],"genre_scores_gemma":[0.04791481,0.00002149176,0.9515136,0.0001559687,0.0002561026,0.00002256907,0.000006342429,0.00004526772,0.00006385335],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2580122,"threshold_uncertainty_score":0.9996322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.066060017546595,"score_gpt":0.3008630341943564,"score_spread":0.2348030166477614,"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."}}