Data from: A temporally intensive survey of bacterial communities of Brassica napus genotypes grown in three environments
Bibliographic record
Abstract
Soil bacterial communities play vital roles in nutrient cycling and plant health. Breeding staple crops to have more robust microbiomes may be a sustainable way to improve crop yield without increasing inputs, leading to better global food security. We collected root and rhizosphere soil samples from sixteen genotypes of canola weekly for ten weeks at one site in 2016 and at three time points across three sites in 2017. We sequenced the 16S ribosomal RNA gene generating a total of 127.7 million reads. The data shows that rhizosphere communities are more diverse than corresponding root communities. Beta diversity analysis demonstrates both temporal and site-to-site differences in community structure. Using this dataset, these and other aspects of the canola microbiome characterization can be explored to advance our understanding of genotype by environment interactions This is a large temporally and spatially rich dataset, which will further our understanding of bacterial communities associated with canola. These data will be used in a variety of other projects, with the goal of enhancing agricultural sustainability.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 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 teacher head, 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".