{"id":"W2023019272","doi":"10.1109/scam.2011.23","title":"Recovering a Balanced Overview of Topics in a Software Domain","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Domain engineering; Domain analysis; Domain (mathematical analysis); Computer science; Feature-oriented domain analysis; Granularity; Domain model; Reuse; Identification (biology); Software engineering; Source code; Software; Code (set theory); Business domain; Data mining; Software development; Data science; Software construction; Programming language; Domain knowledge; Engineering; Business rule","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":[0.000239557,0.00006397937,0.0001249209,0.0001148337,0.000008526588,0.00001186424,0.0005654263,0.00003533247,0.00006477344],"category_scores_gemma":[0.0002489048,0.00005965321,0.00003168599,0.0004330806,0.00001215273,0.0001870357,0.0002326358,0.00008891715,0.00001387925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003670276,"about_ca_system_score_gemma":0.00003824565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001368456,"about_ca_topic_score_gemma":0.00002781076,"domain_scores_codex":[0.9992849,0.00002133584,0.0001570056,0.0001739483,0.0001646931,0.0001981176],"domain_scores_gemma":[0.9993656,0.0001322286,0.00002199933,0.0004082894,0.00003023702,0.00004162227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002215771,0.0002560865,0.7193665,0.0005511317,0.00003562533,0.0001444231,0.007154927,0.0002184144,0.0009844879,0.09684731,0.000502649,0.1739163],"study_design_scores_gemma":[0.0008109577,0.0001731572,0.9642662,0.0002683279,0.000001332705,0.00001733751,0.00003464515,0.003731492,0.008752606,0.0194045,0.002177829,0.0003615691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2338893,0.0002588498,0.7637832,0.00005632716,0.0001596228,0.0001228309,6.145435e-7,0.0002041019,0.001525159],"genre_scores_gemma":[0.4041516,0.00004178891,0.5955062,0.00005194218,0.00001490257,0.00001582233,2.474289e-7,0.000007793658,0.0002097785],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2448998,"threshold_uncertainty_score":0.2432587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05962982282458056,"score_gpt":0.282705894301885,"score_spread":0.2230760714773044,"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."}}