Bibliographic record
Abstract
It has long been known that the microbial component of terrestrial ecosystems provides the capacity for nutrient and elemental cycling and other key ecosystem services. Advances in DNA sequencing technology and analytical capacity continue to reveal novel insights into the structure and dynamics of these microbial ecosystems. These insights have led to an increasing appreciation of the importance of the microbial species that associate with multicellular organisms, including plants. The relationship between the multicellular host and its microbiota is sufficiently interdependent that the plant has come to be understood as a “holobiont” that encompasses a multitude of prokaryotic and eukaryotic species. This expands the traditional view of what constitutes an independent organism to include a collectivity of species that coexist for mutual benefit. The concept of organismality presented by Queller and Strassman goes even further than that, arguing that organisms can be defined as collectivities of cells or species that share a common purpose, regardless of genetic identity. As applied to plants, the ideas elaborated by Simard and others that plant communities and their associated mycorrhizal networks form an interconnected collectivity with cognitive functions also fits into this theme. Stephen Jay Gould discussed ideas of what constitutes an organism in the 1990s. But the ideas themselves are even older than that, dating all the way back to Charles Darwin himself. Incredibly, the connections among these philosophical concepts were anticipated in a science fiction story written by Isaac Asimov over 70 years ago.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".