Chromosome-level genome assembly of Triticum turgidum var 'Kronos' additional datasets
Bibliographic record
Abstract
This data is made available under the Toronto Agreement. All of the data listed here is available under the prepublication data sharing principle of the Toronto agreement (1). By using this data, you agree to: respect the rights of the data producers and contributors to analyze and publish the first global analyses and certain other reserved analyses of this data set in a peer-reviewed publication. not redistribute, release, or otherwise provide access to the data to anyone outside of the group, until the data has been published & submitted to the public data repositories. contact the authors to discuss any plans to publish data or analyses that utilize this data to avoid the overlap of any planned analyses. fully cite the prepublication data along with any applicable versioning details. understand that this data as accessed is precompetitive and is not patentable in its present state. This agreement does not expire by time but only upon publication of the first global analysis by the data producers and contributors.(1) Toronto International Data Release Workshop Authors. Prepublication data sharing. Nature 461, 168–170 (2009). https://doi.org/10.1038/461168a If you have questions about the use of this dataset, please contact Ksenia Krasileva: kseniak [at] berkeley.edu Summary of the datasetsRepetitive elements were initially annotated using HiTE v3.0.0 and this repeat library was used to soft-mask the reference genomes v1.0 and v1.1. This dataset can be found in 01.HiTE.zip. After generating the reference annotation v2.0, we re-annotated repetitive elements with EDTA v2.2.2. To enhance repeat prediction and classification, complete and consensus repeats for Triticum were retrieved from the TREP database and included as curated libraries. Additionally, classified repeats from HiTE were integrated as RepeatModeler libraries. To prevent over-masking, the coding sequences of the v2.0 annotations were also provided. The outputs can be found in 02.EDTA.zip. Acknowledgement This work has been funded by the United States Department of Agriculture - National Institute for Food and Agriculture Award (2021-67013-35726). Please, feel free to reach out to us regarding this datasets
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.025 |
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".