Referee report. For: Squalomix: shark and ray genome analysis consortium and its data sharing platform [version 1; peer review: 1 approved]
Bibliographic record
Abstract
The taxon Elasmobranchii (sharks and rays) contains one of the long-established evolutionary lineages of vertebrates with a tantalizing collection of species occupying critical aquatic habitats. To overcome the current limitation in molecular resources, we launched the Squalomix Consortium in 2020 to promote a genome-wide array of molecular approaches, specifically targeting shark and ray species. Among the various bottlenecks in working with elasmobranchs are their elusiveness and low fecundity as well as the large and highly repetitive genomes. Their peculiar body fluid composition has also hindered the establishment of methods to perform routine cell culturing required for their karyotyping. In the Squalomix consortium, these obstacles are expected to be solved through a combination of in-house cytological techniques including karyotyping of cultured cells, chromatin preparation for Hi-C data acquisition, and high fidelity long-read sequencing. The resources and products obtained in this consortium, including genome and transcriptome sequences, a genome browser powered by JBrowse2 to visualize sequence alignments, and comprehensive matrices of gene expression profiles for selected species are accessible through https://github.com/Squalomix/info .
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 | 0.011 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.700 | 0.376 |
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".