Power of Attorney for Research: The Need for a Clear Legal Mechanism
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
Journal Article Power of Attorney for Research: The Need for a Clear Legal Mechanism Get access Ann M. Heesters, Ann M. Heesters *Corresponding author: Ann M. Heesters, University Health Network, 550 University Avenue, Toronto, Ontario M5G 2A2, Canada. Email: ann.heesters@uhn.ca Search for other works by this author on: Oxford Academic PubMed Google Scholar Daniel Z. Buchman, Daniel Z. Buchman Search for other works by this author on: Oxford Academic PubMed Google Scholar Kyle W. Anstey, Kyle W. Anstey Search for other works by this author on: Oxford Academic PubMed Google Scholar Jennifer A.H. Bell, Jennifer A.H. Bell Search for other works by this author on: Oxford Academic PubMed Google Scholar Barbara J. Russell, Barbara J. Russell Search for other works by this author on: Oxford Academic PubMed Google Scholar Linda Wright Linda Wright Search for other works by this author on: Oxford Academic PubMed Google Scholar Public Health Ethics, Volume 10, Issue 1, April 2017, Pages 100–104, https://doi.org/10.1093/phe/phw035 Published: 25 August 2016
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 | 0.133 | 0.407 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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