An intensive multilocation temporal dataset of fungal communities in the root and rhizosphere of Brassica napus
Bibliographic record
Abstract
The plant microbiome has been recently recognized as a plant phenotype to help in the food security of the future population. However, global plant microbiome datasets are insufficient to be used effectively for breeding this new generation of crop plants. We surveyed the diversity and temporal composition of fungal communities in the root and rhizosphere of Brassica napus, the world's second largest oilseed crop, weekly in eight diverse lines at one site and every three weeks in sixteen lines, at three sites in 2016 and 2017 in the Canadian Prairies. 14,944 unique amplicon sequence variants (ASV) were detected based on the internal transcribed spacer region, with an average of 43 ASVs per root and 105 ASVs per rhizosphere sample. Temporal, site-to-site, and line-driven variability were key determinants of fungal community structure. This dataset is a valuable resource to systematically extract information on the belowground microbiome of diverse B. napus lines in different environments, at different times in the growing season, in order to adapt effective varieties for sustainable crop production systems.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".