Bibliographic record
Abstract
VCF file of 2,799,166 single nucleotide polymorphism (SNP) markers positioned onto the Chinese Spring reference assembly RefSeq v2.1 developed by the International Wheat Genome Sequence Consortium (IWGSC; Zhu et al., 2021). These SNPs were lifted from the 1,000 wheat exome project, originally positioned onto RefSeq v1.0 (He et al., 2019). The SNP projection from RefSeq v1.0 onto RefSeq v2.1 was accomplished using LiftOff (Shumate and Salzberg, 2021). References He F, Pasam R, Shi F, Kant S, Keeble-Gagnere G, Kay P, Forrest K, Fritz A, Hucl P, Wiebe K, et al: <strong>Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome.</strong> <em>Nature Genetics </em>2019, <strong>51:</strong>896-904. Shumate A, Salzberg SL: <strong>Liftoff: accurate mapping of gene annotations.</strong> <em>Bioinformatics </em>2021, <strong>37:</strong>1639-1643. Zhu T, Wang L, Rimbert H, Rodriguez JC, Deal KR, De Oliveira R, Choulet F, Keeble-Gagnère G, Tibbits J, Rogers J, et al: <strong>Optical maps refine the bread wheat Triticum aestivum cv. Chinese Spring genome assembly.</strong> <em>The Plant Journal </em>2021, <strong>107:</strong>303-314..
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.074 |
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".