{"id":"W39351959","doi":"10.1002/alz.14253","title":"Compositions of Concurrent Processes","year":2006,"lang":"en","type":"article","venue":"Communicating Process Architectures","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; National Institute on Aging; Fujirebio Europe; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Alzheimer's Drug Discovery Foundation; Merck; Eli Lilly and Company; Servier; GE Healthcare; BioClinica","keywords":"Concurrency; Computer science; Simultaneity; Programming language; Semantics (computer science); Abstraction; Communicating sequential processes; Extension (predicate logic); Theoretical computer science; Observer (physics); Concurrency control; Operational semantics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003150105,0.0001310691,0.0001807294,0.000115434,0.000245533,0.00006056353,0.002357126,0.00004030155,0.000003711635],"category_scores_gemma":[0.0002520462,0.000117949,0.00004198519,0.0006153029,0.000221414,0.0001261494,0.0003769314,0.0002285768,0.000002914357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000148863,"about_ca_system_score_gemma":0.0001001129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004684171,"about_ca_topic_score_gemma":0.00002041003,"domain_scores_codex":[0.9988014,0.0001654826,0.0003883654,0.0002128759,0.0002370611,0.0001947832],"domain_scores_gemma":[0.9980135,0.0003158699,0.0003209834,0.001045758,0.0002696712,0.00003419378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002373172,0.001142127,0.005934719,0.002679282,0.00005524034,0.000001910958,0.01205067,0.03345311,0.01909902,0.6870875,0.0002334394,0.2382393],"study_design_scores_gemma":[0.001005231,0.0003834784,0.02121183,0.001029124,0.00004144069,0.0001185168,0.0002676944,0.1279977,0.6389061,0.204061,0.003887799,0.001090043],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09873667,0.002349556,0.8867406,0.0004743687,0.00008629041,0.0002769654,0.000008386541,0.0003586863,0.01096851],"genre_scores_gemma":[0.6686103,0.000008663398,0.3312674,0.0000327294,0.00001645803,0.00004298039,0.00000714264,0.000006824439,0.000007529546],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6198071,"threshold_uncertainty_score":0.4809821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02591563103077952,"score_gpt":0.3251006370316497,"score_spread":0.2991850060008702,"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."}}