{"id":"W2129306832","doi":"10.1007/978-3-642-02059-9_6","title":"AspectOptima: A Case Study on Aspect Dependencies and Interactions","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"AspectJ; Aspect-oriented programming; Computer science; Programming language; Separation of concerns; Structuring; Consistency (knowledge bases); Atomicity; Software engineering; Set (abstract data type); Concurrency; Software; Artificial intelligence; Database transaction","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"],"consensus_categories":[],"category_scores_codex":[0.0008886139,0.0005777634,0.0005667508,0.001014802,0.0003065773,0.0004747009,0.001568774,0.0001575431,0.000004994627],"category_scores_gemma":[0.0005042573,0.0005204519,0.00008364263,0.0005011616,0.0003489651,0.0006471325,0.001009844,0.001183998,0.00001281238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417687,"about_ca_system_score_gemma":0.0001856188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000267228,"about_ca_topic_score_gemma":0.0001493161,"domain_scores_codex":[0.9967217,0.00007198152,0.0004124076,0.001603358,0.0006621812,0.0005283314],"domain_scores_gemma":[0.9959667,0.002170073,0.0001870695,0.001384816,0.0001441487,0.0001472147],"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":[0.000005764861,0.00008415528,0.00003445922,0.00001229181,0.00002009223,0.008053523,0.002627537,0.1564462,0.00004223564,0.005562488,0.000005278628,0.8271059],"study_design_scores_gemma":[0.001414142,0.00462756,0.001399713,0.0008883016,0.00006514753,0.03004437,0.00002998695,0.2365851,0.001543353,0.7190249,0.000751299,0.003626137],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001191599,0.0002778748,0.9951738,0.0002420798,0.001280845,0.0004843973,0.000002277247,0.0004919406,0.0008551546],"genre_scores_gemma":[0.2456571,0.00001678071,0.7535943,0.00029035,0.0001999315,0.00001075478,4.694018e-7,0.00002633153,0.0002039421],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8234798,"threshold_uncertainty_score":0.9997247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05071402008353255,"score_gpt":0.3171438200705883,"score_spread":0.2664297999870558,"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."}}