Measurement of arthropod body composition using quantitative magnetic resonance
Bibliographic record
Abstract
Abstract Quantitative magnetic resonance (QMR) is a new technology for measuring the body composition (wet lean mass, fat mass, and total body water mass) of unrestrained and unanesthetized animals. We conducted a validation study using two species of crayfish (mass range 5.5–27 g), American lobsters (680–732 g), and Madagascar hissing cockroaches (6.5–14 g) to assess the utility ofQMRfor quantifying the body composition of crustaceans and other large arthropods. A comparison of crayfish, lobster, and cockroach wet lean, fat, and body water masses calculated byQMRwith those obtained from the traditional chemical extraction method demonstrates thatQMRis a valid technology for analysis of wet lean mass and body water. Fat mass could not be accurately predicted, although this might be improved with the use of aQMRanalyzer designed specifically for animals of low fat content.QMRanalysis allows rapid (<4 min) and non‐destructive determination of body composition in field and lab environments, enabling researchers to conduct longitudinal studies and to increase the ethicality and practicality of studying rare or threatened species.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".