{"id":"W3216702545","doi":"","title":"Modeling and Verifying Timed Compensable Workflows and an Application to Health Care","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Workflow; Computer science; Software engineering; Reliability (semiconductor); Model checking; Semantics (computer science); Petri net; Workflow management system; Programming language; Formal verification; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.0003533225,0.000120143,0.0001648093,0.0003111573,0.0003261483,0.0003006504,0.0002478223,0.00003267618,0.000002162343],"category_scores_gemma":[0.00002196778,0.0001089093,0.00001120636,0.001043751,0.00006766238,0.0007979784,0.000215501,0.00009393071,0.000003873974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002569287,"about_ca_system_score_gemma":0.00003424926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001787602,"about_ca_topic_score_gemma":0.0005406284,"domain_scores_codex":[0.9989064,0.000005649562,0.0001620935,0.0004968268,0.0001675947,0.0002614291],"domain_scores_gemma":[0.9995458,0.00001087811,0.00005225405,0.0002076118,0.0001502509,0.00003324203],"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":[0.000008154413,0.00001730497,0.004297906,0.00008713582,0.000001527014,6.786976e-7,0.001757724,0.3660058,0.0001152776,0.0001258559,5.758046e-7,0.6275821],"study_design_scores_gemma":[0.0001013957,0.000009357908,0.0007431705,0.00005883527,0.00000495957,9.541195e-7,0.00001778986,0.9964743,0.00003992625,0.002397551,0.00001560146,0.0001361765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2638574,0.0002164558,0.735401,0.0003074927,0.00005565102,0.00009691736,1.555672e-7,0.00004688707,0.00001805878],"genre_scores_gemma":[0.9000685,0.000005723417,0.09728719,0.002427929,0.0001920509,0.000007232126,0.000003143785,0.000008171311,1.201529e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6381137,"threshold_uncertainty_score":0.4441193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675500333622475,"score_gpt":0.2615123976298007,"score_spread":0.2347573942935759,"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."}}