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
Welcome to the Fall 2014 edition of the Jefferson Interprofessional Education and Care Newsletter. It has been a busy Fall at Jefferson and we are excited to share several new developments which have been pushing the envelope in IPE. In October, we hosted our 4th biennial conference, Interprofessional Care for the 21st Century: Redefining Education and Practice. This year we had a record number of conference participants and presenters joining us from a variety of national and international academic and service organizations. Our keynote speakers, Dr. George Thibault, President, Josiah Macy Jr Foundation; Dr. Barbara Brandt, Director, National Center for Interprofessional Practice and Education at the University of Minnesota; Dr. John Gilbert, Principal & Professor Emeritus, University of British Columbia College of Health Disciplines, Co-Chair of the Canadian Interprofessional Health Collaborative; and a team from the Veterans Administration, including Dr. Malcolm Cox, Dr. Stuart Gilman, Dr. Richard Stark and Dr. Kathryn Rugen, collectively challenged and inspired us to re-conceptualize interprofessional education and collaborative practice opportunities for students as we prepare them for a healthcare delivery system that will focus on the triple aim of improving a patient’s care experience, improving the health of patient populations, and reducing the per capita cost of healthcare. One of the articles that follows will highlight the conference presentation of the innovative work of Dr. Susanne Boyle from the University of Glasgow, Scotland and her colleagues. Dr. Boyle’s team explored the area of augmented reality and its applicability to enhancing online interprofessional education through virtual communities.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.153 | 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