Bibliographic record
Abstract
s Van Walleghen E, Orr J, Morrill J, Gentile C, Johnson S, Davy B. Is Water Consumption an Effective Strategy to Reduce Meal Energy Intake? Presented at the 2005 North American Association for the Study of Obesity Annual Scientific Meeting in Vancouver, B.C., October, 2005. Van Walleghen E, Orr J, Davy B. Gender Differences in Energy Intake Regulation. Presented at the 22 Annual SCAN Symposium in Nashville, TN, March 24-26, 2006. Gilmour K, Van Walleghen E, Kealey E, Von Kaenel S, Bessesen D, Johnson S, Davy B. Influence of Age, Gender and Physical Activity Habits on Eating Behavior in Nonobese Adults. Presented at the 22 Annual Research Symposium, Graduate Student Assembly, Virginia Tech, March 29, 2006. Dennis E, Van Walleghen E, Orr J, Gentile C, Davy K, Davy B. Aging, Physical Activity and Resting Metabolic Rate. Presented at the 22 Annual Research Symposium, Graduate Student Assembly, Virginia Tech, March 29, 2006. Davy B, Orr S, Van Walleghen E. Gender Differences in Energy Intake Regulation Among Healthy Older Adults. To be presented at the 2006 North American Association for the Study of Obesity Annual Scientific Meeting in Boston, MA, October, 2006. Awards and Honors Virginia Polytechnic Institute and State University Outstanding Graduate Student, Department of Human Nutrition, Foods, and Exercise, 2006 Graduate Research Development Project Grant, Graduate Student Assembly, 2005 University of Illinois Outstanding Senior in Human Nutrition, Department of Food Science and Human Nutrition, 2000
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".