Who won the Winter 2010 Olympics? A quest into priorities and rankings
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
Abstract During and at the end of Olympic games, we are always given the number of gold, silver and bronze medals won by each country and often the total number won as an indicator of the surmised winner. The groups that report the medal count in this manner indicate that they believe all medals are the same, regardless of the kind of medal involved. Perhaps one reason it is done this way is because there has not been a scientific way to assign appropriate weights to each type of medal. This paper explores use of the measurement theory, the Analytic Hierarchy Process (AHP), to quantify the values of gold, silver and bronze medals and use these values to compute the total value of the medals won by the leading countries in order to determine which country may be considered the winner of the 21st Winter Olympics held February 12–28, 2010, in Vancouver, Canada. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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