Additional file 1: Table S1. of Host species identity, site and time drive temperate tree phyllosphere bacterial community structure
Bibliographic record
Abstract
Description of the four study sites during the summer of 2013 (Canadian historical climate data, http://climate.weather.gc.ca/ ). Table S2. Taxonomic identity of the 19 core microbiome OTUs across the 142 trees sampled. Taxonomic identification was based on a BLAST against the greengenes database with a minimum cutoff of 50 % confidence required for assignment to a given taxonomic group. Table S3. Significative associations between bacterial taxonomic groups (a-Phylum, b-Class, c-Order, d-Family and e-OTUs) and tree species (LEfSe analyses). Scores identify which clades have the greatest explanatory power on differences between communities. Table S4. Significative associations between bacterial taxonomic groups (a-Phylum, b-Class, c-Order, d-Family and e-OTUs) with tree species classified between angiosperms and gymnosperms (LEfSe analyses). Scores identify which clades have the greatest explanatory power on differences between communities. Table S5. Taxonomic and functional trait information of the five tree species used in this study. Sources for functional trait information are described in the main text. Figure S1. Location of the four sites sampled during summer 2013 across the temperate forest of Quebec’s province. Figure S2. Collector’s curve (mean 95 % confidence interval) of bacterial phyllosphere operational taxonomic units (OTUs; 97 % sequence similarity cut-off) richness versus number of trees sampled in the temperate forest in 2013. (DOC 1640 kb)
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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.864 | 0.159 |
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".