Are Human Intestinal Eukaryotes Beneficial or Commensals?
Bibliographic record
Abstract
Since the advent of microbiology, it has been well known that each human body hosts a multitude of microbes. The magnitude of our microbial system is best reflected by the widely discussed ratio of one human cell to ten microbes. Indeed, humans and other mammals live in a consortium composed of vast arrays of viruses (these are typically called the virome), archaea and bacteria (i.e., the microbiome), along with fungi and other uni- and multicellular eukaryotes (protists and helminths, respectively) historically thought of as “parasites.” It was the advent of next generation sequencing (NGS) that first allowed deeper insight not only into the composition of this “microbial zoo” but also its dynamics in relation to age, diet, health, sex, and geographic location of the host. Attention has focused primarily on the bacterial microbiome, which constitutes the most abundant and diverse segment of the human intestinal ecosystem./nHowever, we argue that eukaryotes play important, but largely unrecognized roles and that there is much to gain by turning our attention to eukaryotic members of the gut/necosystem.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".