Peer Review #3 of "Tree phyllosphere bacterial communities: exploring the magnitude of intra- and inter-individual variation among host species (v0.1)"
Bibliographic record
Abstract
Background.The diversity and composition of the microbial community of tree leaves (the phyllosphere) varies among trees and host species and along spatial, temporal, and environmental gradients.Phyllosphere community variation within the canopy of an individual tree exists but the importance of this variation relative to among-tree and among-species variation is poorly understood.Sampling techniques employed for phyllosphere studies include picking leaves from one canopy location to mixing randomly selected leaves from throughout the canopy.In this context, our goal was to characterize the relative importance of intraindividual variation in phyllosphere communities across multiple species, and compare this variation to inter-individual and interspecific variation of phyllosphere epiphytic bacterial communities in a natural temperate forest in Quebec, Canada.Methods.We targeted five dominant temperate forest tree species including angiosperms and gymnosperms: Acer saccharum, Acer rubrum, Betula papyrifera, Abies balsamea and Picea glauca.For one randomly selected tree of each species, we sampled microbial communities at six distinct canopy locations: bottom-canopy (1-2m height), the four cardinal points of midcanopy (2-4m height), and the top-canopy (4-6m height).We also collected bottom-canopy leaves from five additional trees from each species.Results.Based on analysis of bacterial community structure measured via Illumina sequencing of the bacterial 16S gene, we demonstrate that 65% of the intra-individual variation in leaf bacterial community structure could be attributed to the effect of inter-individual and inter-
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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 | 0.010 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.338 | 0.151 |
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".