{"id":"W2060537934","doi":"10.1145/638750.638770","title":"Declarative Meta Programming to Support Software Development","year":2003,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Software engineering; Software development; Context (archaeology); Software; Software development process; Programming language","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005374243,0.0003886035,0.0004188503,0.0002411139,0.0001879314,0.0002222732,0.0009354711,0.0001199575,0.00005350456],"category_scores_gemma":[0.04171073,0.0003607242,0.0001459666,0.0006175225,0.000009871541,0.0005278632,0.000286597,0.0001765478,0.0002046921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001281276,"about_ca_system_score_gemma":0.0001594794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001788545,"about_ca_topic_score_gemma":0.00001250977,"domain_scores_codex":[0.9977452,0.00005126155,0.0004743878,0.0006500264,0.0004714889,0.0006075998],"domain_scores_gemma":[0.9922095,0.006284443,0.0001185439,0.0009226864,0.000167299,0.0002975055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002198373,0.0007438997,0.5488358,0.0009954418,0.003027814,0.0002860226,0.0324451,0.02342326,0.005951182,0.01134429,0.00516637,0.3677588],"study_design_scores_gemma":[0.001634382,0.0006466417,0.1620814,0.0003616489,0.0003450075,0.0001766856,0.00007881078,0.0005548279,0.1772404,0.0001039342,0.6527357,0.004040576],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03895744,0.0002557764,0.958387,0.00009433783,0.0006046737,0.0005453265,0.000003973418,0.001149001,0.000002480933],"genre_scores_gemma":[0.4163291,0.000001499937,0.5831656,0.0001196049,0.00003362723,0.0001948874,0.00001051106,0.00003027482,0.0001149219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6475694,"threshold_uncertainty_score":0.9998845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05084089791429167,"score_gpt":0.2639148135958985,"score_spread":0.2130739156816068,"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."}}