{"id":"W2081946494","doi":"10.5555/776816.776859","title":"Design pattern rationale graphs: linking design to source","year":2003,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Software design pattern; Computer science; Design pattern; Structural pattern; Flexibility (engineering); Pattern language (formal languages); Source code; Software engineering; Code (set theory); TRACE (psycholinguistics); Representation (politics); Human–computer interaction; Programming language; Software design; Software development; Software","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":[0.007383467,0.002019392,0.0006745569,0.008280721,0.001388996,0.004174421,0.002714725,0.002600588,0.009481423],"category_scores_gemma":[0.04209631,0.001922724,0.001720812,0.005549149,0.00200124,0.007081613,0.004639205,0.002747055,0.003297289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456007,"about_ca_system_score_gemma":0.003813456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00704795,"about_ca_topic_score_gemma":0.008751123,"domain_scores_codex":[0.9937502,0.002692861,0.0005888534,0.0006374868,0.002132431,0.0001980662],"domain_scores_gemma":[0.9744899,0.01507856,0.002156273,0.005043908,0.002851502,0.0003798661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001712245,0.0003703762,0.004426539,0.001795019,0.0001801985,0.001339846,0.00424583,0.02878843,0.007739172,0.2361108,0.04775683,0.6670758],"study_design_scores_gemma":[0.0001570903,0.0001404964,0.001755868,0.001151596,0.0001605204,0.001060231,0.0009671846,0.1679334,0.01773034,0.3910806,0.4176551,0.0002076619],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002302245,0.0001849772,0.9820309,0.0005955527,0.00006609637,0.0003675231,0.0008425552,0.009206885,0.004403243],"genre_scores_gemma":[0.0256774,0.0006833629,0.962785,0.0003547849,0.00004593555,0.0007075501,0.003620316,0.002633862,0.003491884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009481423,"threshold_uncertainty_score":0.03904796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05024159134126945,"score_gpt":0.2606800102843191,"score_spread":0.2104384189430496,"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."}}