Evaluation datasets and results of the paper "A Framework for Measuring the Quality of Business Process Simulation Models"
Bibliographic record
Abstract
Datasets and files used in the evaluation of the publication entitled "A Framework for Measuring the Quality of Business Process Simulation Models", where: BPS-models/: folder containing the BPS models used in the evaluation (the BPS models discovered by ServiceMiner are not included due to privacy reasons). The BPS models discovered by SIMOD are composed of i) a BPMN file with the process model structure, and ii) a JSON file with the parameters of the simulation. These files correspond to the format of Prosimos simulation engine (https://prosimos.cloud.ut.ee/). The BPS models of the Loan Application and Procure to Pay processes are composed of a BPMN file with both the process model structure and parameters, corresponding to the format of the BIMP simulator used in APROMORE (https://apromore.com/). measures/: folder containing the distance values of each measure reported in the paper. original-event-logs/: folder containing the (train and test) event logs used in the evaluation. simulated-logs/: folder containing the simulated logs evaluated in the paper (synthetic, SIMOD, and ServiceMiner). ComputeLogDistance.py: script to compute the distance measures proposed in the paper. To evaluate the distance measures of a set of simulated event logs in the folder simulated_logs/ against the test log test_event_log.csv.gz, run: python ComputeLogDistance.py -cfld test_event_log.csv.gz simulated_logs/ *The flag -cfld is optional, due to the high computational complexity of the CFLD measure. WARNING: set the column names of each log accordingly (where log_1_ids are the IDs of the test log, and log_2_ids the IDs of the simulated logs). Examples: # Column IDs for the (train/test) real-life logs, and the SIMOD simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='start_time', end_time='end_time', resource='resource' ) # Column IDs for the Loan Application and Procure to Pay simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='Start_Time', end_time='End_Time', resource='resource' ) # Column IDs for the ServiceMiner simulated logs. EventLogIDs( case='case_id', activity='Activity', start_time='start_time', end_time='end_time', resource='Resource' )
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".