Proceedings of the 6th International Conference of Applied Operational Research.
Bibliographic record
Abstract
Operational Research is an important scientific discipline with many new theoretical developments and practical applications. The International Conference on Applied Operational Research (ICAOR) is an annual forum bringing together academics and practitioners from around the world to discuss the most recent developments in operational research and management science (OR/MS). The conference covers all aspects of our subject, but with a particular emphasis on applications. This year, the sixth event in our planned series of conferences – ICAOR 2014 takes place in the city of Vancouver, Canada. We received quality submissions from approximately 21 countries around the world and finally could accept 28 papers for presentation at the conference and publication in these proceedings. The papers that appear in this volume were carefully and thoroughly refereed. Our sincere thanks go to the members of the scientific programme committee who gave a significant amount of their valuable time to this task. We are also very grateful to all those who have helped in organising the conference. We are sure that their contributions will add significantly to the success of the conference. We very much hope that you will enjoy the conference programme and the planned social events. We wish you all a very pleasant stay in Vancouver and trust that you will find the conference to be of value and leave us having made many new friends.
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.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".