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
I would like to thank all the members of the Agar Lab for their support and thoughtful discussions. Dr. Jeffrey Agar has provided me an extraordinary opportunity by letting me join his group and opened the doors of science by pushing me harder to succeed and be better on every project I worked on. I would especially like to thank Jared Auclair and Joseph Salisbury for their efforts in training me, mentoring me on a daily basis, and supporting me with various ways throughout my senior thesis. I would also like to thank all the members of Petsko-Ringe Lab for the use of their instruments and their thoughtful discussions during the preparation of my thesis defense. I would like to thank Dr. Rebecca Chafel and Liam Putney for all the work they have done at the Foster Lab to ensure the maintenance and ongoing of our mice colony, training and supervising me throughout our in vivo experiments.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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