Genomic insights into metabolic flux in ruby-throated hummingbirds
Bibliographic record
Abstract
Hummingbirds employ hovering flight, displaying the highest wingbeat frequencies of any bird and sustaining the highest metabolic rates among all vertebrates. Their tissues are very well adapted to sustain efficient and rapid metabolic shifts. Hummingbirds oxidize ingested nectar sugars directly to fuel when foraging but have to switch to oxidizing stored lipids derived from ingested sugars during the night or long-distance migratory flights. The liver plays a vital role in moderating energy homeostasis and the rapid flux from glycolytic to lipogenic metabolism, demonstrated by a remarkable ability to sustain high rates of metabolism using endogenous lipids. The flight muscle must maintain rates as much as 55× greater than the maximum rates observed in any non-flying mammals for transport, uptake and oxidation of circulating sugars. Yet, understanding how this organism moderates energy turnover is hampered by a lack of information regarding how relevant enzymes differ in sequence, expression, and regulation. We generated a chromosome level de novo genome assembly of the ruby-throated hummingbird and used hybrid long and short-read sequencing methodologies for a comprehensive transcriptome assembly and annotation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".