{"id":"W1549677228","doi":"10.1007/3-540-45821-2_6","title":"A Protocol Stack Development Tool Using Generative Programming","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Protocol (science); Protocol stack; Sketch; Communications protocol; Generative grammar; Distributed computing; Programming language; Reprogramming; Stack (abstract data type); Artificial intelligence; Operating system; Algorithm","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":[0.001084551,0.0007033445,0.0006078723,0.0007102647,0.0003355486,0.0006163915,0.00272133,0.0003070612,0.000012006],"category_scores_gemma":[0.000318069,0.0006394522,0.00009816549,0.0006806715,0.0004419865,0.0008338389,0.00176001,0.0008632797,0.000019359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000847753,"about_ca_system_score_gemma":0.000683327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002216162,"about_ca_topic_score_gemma":0.000005436047,"domain_scores_codex":[0.9956857,0.00006389544,0.0006682175,0.001671254,0.001015204,0.0008957215],"domain_scores_gemma":[0.9974831,0.0005212439,0.0003466696,0.001211822,0.0003029576,0.0001342365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002338412,0.00001566683,0.000005060459,0.00005537897,0.00000907282,0.00007238978,0.001014569,0.3222869,0.0001299168,0.001787028,0.000002070251,0.6746196],"study_design_scores_gemma":[0.0005740641,0.0002497988,0.00002424447,0.000975855,0.00000754548,0.00015864,3.051863e-7,0.8803223,0.01119714,0.08950914,0.01490113,0.002079812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001366619,0.00004746705,0.9809588,0.00005862604,0.0007193341,0.01752842,9.791972e-7,0.0005132355,0.0001594418],"genre_scores_gemma":[0.0001538789,0.000001683853,0.9956382,0.0001889007,0.0002473289,0.003453276,0.000001024312,0.00004734,0.0002683947],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6725398,"threshold_uncertainty_score":0.9996057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08620018224210127,"score_gpt":0.3249778873774405,"score_spread":0.2387777051353393,"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."}}