{"id":"W3044961859","doi":"10.1145/1041685.1029904","title":"Merging partial behavioural models","year":2004,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Notation; Viewpoints; Process (computing); Consistency (knowledge bases); Sequence (biology); Theoretical computer science; Programming language; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005694921,0.001248147,0.0009000628,0.001900648,0.001158028,0.003128262,0.002824952,0.001594851,0.003957551],"category_scores_gemma":[0.01749393,0.00139788,0.004585409,0.001657527,0.002009181,0.006099585,0.006153015,0.002440472,0.0007977632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001757241,"about_ca_system_score_gemma":0.003296512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008923233,"about_ca_topic_score_gemma":0.01316845,"domain_scores_codex":[0.9915887,0.002415618,0.0008591223,0.001260584,0.003299868,0.0005761234],"domain_scores_gemma":[0.9880459,0.004423427,0.0006848279,0.004577087,0.002014402,0.0002544329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004007544,0.0002781144,0.009306879,0.0009716269,0.0004854353,0.001277311,0.006170994,0.269908,0.02377062,0.5286704,0.003133194,0.1556266],"study_design_scores_gemma":[0.0000583354,0.0002720473,0.001801025,0.000291176,0.000519142,0.0004410444,0.001176631,0.5041139,0.02074468,0.4274305,0.04301931,0.0001322423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01947131,0.0001172638,0.9746054,0.0002015817,0.00002442699,0.0002235948,0.0003695289,0.001061078,0.003925747],"genre_scores_gemma":[0.2382516,0.0003967436,0.7539061,0.000185474,0.00002969314,0.0005511374,0.002542489,0.0004097149,0.003727079],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008923233,"threshold_uncertainty_score":0.03011799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06001615267200049,"score_gpt":0.2738289857814312,"score_spread":0.2138128331094307,"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."}}