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Record W1991178126 · doi:10.1242/jeb.02762

FAT PROCESSING CHAMPIONS

2007· article· en· W1991178126 on OpenAlexaboutno aff
Laura Blackburn

Bibliographic record

VenueJournal of Experimental Biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsSandpiperShiveringRespirometerEnergy metabolismBiologyAnimal scienceEcologyZoologyRespirationPhysiology

Abstract

fetched live from OpenAlex

Most migratory birds put other animal athletes to shame, completing journeys thousands of miles long fuelled by energy from their exceptional lipid metabolism. One of these champions is the ruff sandpiper Philomachus pugnax, a shorebird that flies a round trip of up to 30 000 km a year between wintering grounds in Africa and nesting grounds in northern Scandinavia. As Jean-Michel Weber from the University of Ottawa explains,researchers face a problem if they want to study the metabolism of flying birds, as it requires invasive measurements which are very difficult to do once a bird is airborne. So to find out more about a sandpiper's lipid metabolism, Weber and his colleague Eric Vaillancourt took a different approach and studied the birds during shivering, which raises the metabolism but makes it much easier to take measurements(p. 1161).The team made two sets of measurements simultaneously to examine the birds'lipid metabolism. The first set involved using a respirometer to measure the total amount of oxygen the birds used and the amount of carbon dioxide they produced. By comparing the quantities of the two gases, the team could work out which fuel the animal was using: carbohydrate, protein or fat. They found that the birds were getting over 80% of their energy from fat when they were at rest. When they lowered the temperature from 22°C to 5°C for 2 h to induce shivering, they found that the birds' oxygen consumption and carbon dioxide production went up. However the ratio of the two gases stayed the same, showing that the birds were simply using the lipids faster to give them enough energy.The second set of measurements were to find out the rate at which the birds were breaking down lipids. Most fats consist of a glycerol backbone with three fatty acids attached, so the body has to break up the molecules and free the fatty acids that can be used for energy. By measuring the rate that glycerol enters the blood stream, scientists can measure how quickly lipids are being broken down. To measure glycerol production, Vaillancourt carried out delicate operations on the birds, inserting two catheters into two different blood vessels in their necks. They used the first catheter to inject labelled glycerol into the blood stream. By comparing the amount of labelled to unlabelled glycerol in blood samples taken from the second catheter, the team could measure the rate of glycerol production.The team were surprised to find that the rate of lipid breakdown in the birds when they were at 22°C matched the highest rate that had ever been measured in an animal. When they dropped the temperature to induce shivering,they found that the rate of glycerol production in the blood stream stayed the same in the normal and cold conditions, showing that shivering didn't boost the rate of lipid breakdown, just the rate at which the birds used lipids for energy, which they saw from their respirometer measurements. This is probably because the rate of lipid breakdown is so high that it doesn't need to increase under colder conditions, because more than enough fatty acids are being released. The birds' record-breaking lipid metabolism is probably essential to achieve their long migrations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2760.094

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.

Opus teacher head0.015
GPT teacher head0.314
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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