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Additional file 1: Table S1. of Host species identity, site and time drive temperate tree phyllosphere bacterial community structure

2016· article· en· W6977936854 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxonomic rankTemperate rainforestTable (database)Species richnessTaxonPhyllosphereCladeTemperate climate

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.989
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9900.001

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.

Opus teacher head0.017
GPT teacher head0.176
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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