Bibliographic record
Abstract
Abstract The long-term goal of American Mink (Neogale vison) Genome Sequencing Project is to develop novel genomics tools to study the genome biology and evolution of mink. This research agenda is organized around three major goals: 1) development of first chromosome-level genome assembly with high quality for American mink to help understanding the biology and evolution of the order Carnivora, 2) designing the first mink single nucleotide polymorphism (SNP) genotyping array for genomic discovery in mink, and 3) using genomics to understand the genetic architecture of economically important traits in mink. An initial draft of the genome assembly is generated using 2,884,047 PacBio long reads. Integration of Hi-C data into the initial draft led to an assembly with 183 scaffolds and scaffold N50 of 220 Mb. This gap-free genome assembly of American mink (ASM_NN_V1) has a length of 2.68 Gb in which about 98.6% of the whole genome is covered by 15 chromosomes. Significant improvements are observed in genome contiguity, the number of scaffolds, and annotation compared with the first draft of mink genome assembly. A custom genotyping array is developed using the developed mink reference genome and DNA panel composed of 100 whole-genome sequences data of American mink from five color-types. This Affymetrix Mink 70K SNP array created 70,000 SNPs, which is sufficient for conducting genomic studies in the mink research program and beyond. This project would facilitate the discovery of genomic regions, markers and genetic networks underlying economically important traits in American mink, which will contribute novel insights into the genetic architecture of key traits and is a critical step to implement genomic selection in mink breeding programs. The results of this research have the potential to impact the mink industry, especially in North America, and improve the overall performance of the mink industry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
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".