Microbiome ethics, guiding principles for microbiome research, use and knowledge management
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 overarching biological impact of microbiomes on their hosts, and more generally their environment, reflects the co-evolution of a mutualistic symbiosis, generating fitness for both. Knowledge of microbiomes, their systemic role, interactions, and impact grows exponentially. When a research field of importance for planetary health evolves so rapidly, it is essential to consider it from an ethical holistic perspective. However, to date, the topic of microbiome ethics has received relatively little attention considering its importance. Here, ethical analysis of microbiome research, innovation, use, and potential impact is structured around the four cornerstone principles of ethics: Do Good; Don't Harm; Respect; Act Justly. This simple, but not simplistic approach allows ethical issues to be communicative and operational. The essence of the paper is captured in a set of eleven microbiome ethics recommendations, e.g., proposing gut microbiome status as common global heritage, similar to the internationally agreed status of major food crops.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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