{"id":"W2156672158","doi":"10.1109/acom.2007.4","title":"Identifying, Assigning, and Quantifying Crosscutting Concerns","year":2007,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Identification (biology); Modularity (biology); Software engineering; Business process reengineering; Ambiguity; Software quality; Code (set theory); Suite; Quality (philosophy); Software; Software development; Programming language; Engineering; Set (abstract data type)","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":[0.008418346,0.001395846,0.0008133713,0.006870314,0.001152414,0.00187113,0.00110255,0.001063232,0.0006346339],"category_scores_gemma":[0.06985132,0.0006614276,0.0005307397,0.002962185,0.0008092788,0.003016767,0.001808143,0.001032343,0.0002116067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168887,"about_ca_system_score_gemma":0.00226406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003267249,"about_ca_topic_score_gemma":0.007089182,"domain_scores_codex":[0.9871579,0.004417957,0.001711206,0.001625136,0.004727211,0.0003605734],"domain_scores_gemma":[0.9012438,0.04336353,0.02248174,0.008904228,0.02293834,0.001068266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001825671,0.0004741299,0.331059,0.001006827,0.0001856507,0.0005385358,0.003887919,0.02799825,0.07421508,0.007694285,0.0018546,0.5509031],"study_design_scores_gemma":[0.00009514489,0.001254385,0.4081483,0.0004842595,0.000483815,0.002989941,0.003201673,0.3189987,0.2179137,0.02811717,0.01798462,0.0003283319],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5657213,0.000563169,0.4280643,0.0003329042,0.00003455073,0.0006550479,0.0003190275,0.001938538,0.002371165],"genre_scores_gemma":[0.5321544,0.0002127799,0.4655654,0.00007609918,0.00001298999,0.0003305233,0.0004988476,0.0002197289,0.0009291879],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008418346,"threshold_uncertainty_score":0.04452103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08655784220837867,"score_gpt":0.373265497336404,"score_spread":0.2867076551280253,"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."}}