Keeping environmental physiology education up and running during the COVID-19 pandemic
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
The COVID-19 pandemic provoked a need for rapid adaptation of teaching strategies and learning environments. Thus novel approaches, predominantly based on online/virtual platforms are needed to minimize the negative effects of the pandemic on teaching (and learning). Herein we describe our recent web-based symposium series on environmental physiology and ergonomics initiative as an example of such a strategy. We outline the ideas behind this series and its implementation, which could serve as an example of a useful joint interactive virtual educational environment that could be applied to any physiology subspecialty. Based on the feedback received from all stakeholders involved in the process, we strongly believe that such an approach can provide an excellent platform for all educational levels from undergraduate students up to seasoned academics. Importantly, the unrestricted availability (free registration and publication of recordings and student handouts) is an important consideration for the democratization of science and the inclusion of financially less well-supported students and academics.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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