Summary of the 2nd International Workshop on Multi-disciplinary, Open, and IntegRatEd Requirements Engineering (MO2RE) co-located with the 47th IEEE/ACM ICSE 2025
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Requirements Engineering (RE) is a critical sub-field of Software Engineering (SE), involving activities to identify, specify, model, analyze, and validate system needs and constraints. RE plays a fundamental role in the SE process. With the current advances in AI, new opportunities for RE arise to ensure the development of trustworthy AI and to utilize AI to perform various RE-related activities more effectively and efficiently. The workshop on Multi-disciplinary, Open, and IntegRatEd RE (MO2RE) successfully addresses the underrepresentation of the RE within the SE community, raises awareness of RE's diverse aspects, and fosters collaboration. The second edition took place on April 27th, 2025, co-located with the 47th IEEE/ACM International Conference on Software Engineering (ICSE) in Ottawa, Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it