Microbial 16S rRNA gene (DNA) and transcripts (cDNA) along a boreal soil-freshwater-estuary continuum
Bibliographic record
Abstract
This repository stores the processed files of the 16S rRNA sequencing reads (DNA and cDNA) of the La Romaine project, which were processed through the DADA2 pipeline. Files are '.rds' files and/or '.csv' files readable by the open statistical software R. The project is part of the Industrial Research Chair in Carbon Biogeochemistry in Boreal Aquatic systems (CarBBAS Chair) led by Paul A. del Giorgio. Samples were pooled by plate ID and season to be processed by DADA2. The number before each '*_seqtab.rds' file corresponds to a pool. ID details are in "splitdf_new.rds". Raw sequences can be found on SRA under the Bioproject number: PRJNA693020. Intermediate processing files are stored here. And scripts are available on Github. Files are being uploaded as manuscripts are published. Currently available files: 2015-2017: 16S rRNA gene and transcripts (DNA and cDNA) in spring, summer, autumn (shallow sequencing) Part of the manuscript: "Terrestrial connectivity, upstream aquatic history and seasonality shape bacterial community assembly within a large boreal aquatic network". The ISME Journal. 2021.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.036 |
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".