Multiple Criteria Decision Making (MCDM 2017) International Conference Held for a Second Time in Canada
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
The 24th International Conference on Multiple Criteria Decision Making (MCDM 2017) was held at the Telfer School of Management, University of Ottawa, on July 10-14, 2017. This was the second time this conference was held in Canada; the first time being in Whistler in 2004, organized by Bill Wedley. We had a wonderful welcome by the school of management; and the scientific program as well as the social events were outstanding. There is a very good essay about the conference by Sarah Ben Amor (General Chair) at http://www.mcdmsociety.org/newsletters/92017-september-2017 My reviews will be limited to the sessions I attended which were mostly those related to AHP/ANP Theory and Applications. https://doi.org/10.13033/ijahp.v9i2.502
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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.009 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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