Factors Influencing the Turnover and Net Isotopic Discrimination of Hydrogen Isotopes in Proteinaceous Tissue: Experimental Results Using Japanese Quail
Bibliographic record
Abstract
Stable hydrogen isotopes (δ(2)H) are commonly used in studies of animal movement. Tissue that is metabolically inactive after growth (e.g., feathers) provides spatial or dietary information that reflects only the period of tissue growth, whereas tissues that are metabolically active (e.g., red blood cells) provide a moving window of forensic information. However, using δ(2)H for studies of animal movement relies on the assumption that tissue δ(2)H values reflect dietary δ(2)H values, plus or minus a net diet-tissue discrimination value, and that the turnover rate is known for metabolically active tissue. The metabolic rate of an animal may influence both diet-tissue discrimination values and isotopic tissue turnover rate, but this hypothesis has not been tested experimentally. To examine the metabolic hypothesis, an experimental group of 12 male and 15 female captive Japanese quail (Coturnix japonica) was housed at 8.9°C for 90 d to elevate their metabolic rates (mL CO(2) min(-1)), and a control group of 12 male and 13 female quail was housed at room temperature during the same period. For both experimental and control birds, diet-tissue discrimination values were estimated for red blood cells and feathers. To determine turnover rate, experimental and control birds were switched from a (2)H-enriched diet to a (2)H-depleted diet, with red blood cells sampled before and after diet switch. Metabolic rate did not influence red blood cell hydrogen isotope turnover rate (η(2)(p) = 0.24)) or diet-feather isotope discrimination values (η(2)(p) = 0.86). Diet-feather hydrogen isotopic discrimination had a significant sex plus treatment interaction effect; female feathers were depleted in (2)H relative to food regardless of treatment, whereas male feathers were enriched in (2)H. The effect of sex suggested that experimental studies should examine whether coeval males and females differ in blood δ(2)H levels during certain periods of the annual cycle.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".