Blood transcriptomics of captive forest musk deer (Moschus berezovskii) and possible associations with the immune response to abscesses
Bibliographic record
Abstract
Forest musk deer (Moschus berezovskii; FMD) are both economically valuable and highly endangered. A problem for FMD captive breeding programs has been the susceptibility of FMD to abscesses. To investigate the mechanisms of abscess development in FMD, the blood transcriptomes of three purulent and three healthy individuals were generated. A total of ~39.68 Gb bases were generated using Illumina HiSeq 4000 sequencing technology and 77,752 unigenes were identified after assembling. All the unigenes were annotated, with 63,531 (81.71%) mapping to at least one database. Based on these functional annotations, 45,798 coding sequences (CDS) were detected, along with 12,697 simple sequence repeats (SSRs) and 65,536 single nucleotide polymorphisms (SNPs). A total of 113 unigenes were found to be differentially expressed between healthy and purulent individuals. Functional annotation indicated that most of these differentially expressed genes were involved in the regulation of immune system processes, particularly those associated with parasitic and bacterial infection pathways.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".