Sizing Up the Uncultured Microbial Majority
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
Predicting the total number of microbial cells on Earth and exploring the full diversity of life are fundamental research concepts that have undergone paradigm shifts in the genomic era. In this issue, Lloyd and colleagues (K. G. Lloyd, A. D. Steen, J. L. Ladau, J. Yin, and L. Crosby, mSystems 3:e00055-18, https://doi.org/10.1128/mSystems.00055-18, 2018) present results that combine these two concepts by estimating the total diversity of all cells from Earth's environments. Leveraging publicly available amplicon, metagenomic, and metatranscriptomic datasets, they determined that nearly all environments are dominated by uncultured lineages, with the exception of humans and human-associated habitats. They define a new concept: phylogenetically diverse noncultured cells (PDNC). Unlike viable but nonculturable cells (VBNC), PDNC are microorganisms for which traditional isolation techniques may never succeed. Lloyd et al. estimate that the majority of microorganisms in Earth's ecosystems may be PDNC and conclude that culture-independent methods combined with innovative culturing techniques may be required to understand the ecology and physiology of these abundant and divergent microorganisms.
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 | 0.001 | 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) | 0.004 | 0.004 |
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