Bibliographic record
Abstract
This repository contains sequencing data for my paper "Island Biogeography of Cryoconite Hole Bacteria in Antarctica's Taylor Valley and Around the World" (Darcy et al. 2018). This data set includes all the sequencing data that were generated as part of the paper, i.e. the sequences from canada, commonwealth, and taylor glaciers, as well as hole locations and measurements.<br><br>Sequence was done with illumina paired-end technology. reads for r1 and r2 are demultiplexed separately and can be found in r1.tar.gz and r2.tar.gz. metadata for these samples is included as metadata.txt.<br><br>This repository doesn't include copies of data from other studies as part of my paper's global meta analysis. Please see the file global_metadata.txt which includes SAMIDs/ERSIDs that can be used to fetch those data from the ENA (https://www.ebi.ac.uk/ena/browser/home) or SRA (https://www.ncbi.nlm.nih.gov/sra). <br>
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 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 | 0.001 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
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; both teacher heads agree on what is shown here.
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".