Benoit Arsenault On Lifestyle, Lipids and Social Media
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
Benoit Arsenault speaks to Francesca Lake (Managing Editor, Future Science Open Access). Dr Benoit Arsenault obtained his doctoral degree in physiology–endocrinology from Université Laval in Québec City, Canada in 2009. After two postdoctoral fellowships performed at the Academic Medical Center in Amsterdam (The Netherlands) and at the Montreal Heart Institute (Canada), he became Assistant Professor at the Department of Medicine at Université Laval in 2013. Dr. Arsenault is also a research scientist in the cardiology axis at the Quebec Heart and Lung Institute in Canada. The research of Dr. Arsenault's team is focused on high-density lipoprotein (HDL) metabolism, lipoprotein(a), PCSK9, lipid-lowering therapy, atherosclerosis, aortic stenosis and other aspects of the lifestyle-related and inherited risk factors for cardiovascular disease and Type 2 diabetes. Dr. Arsenault is a Senior Editor of Future Science Open Access.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it