The pattern of reproduction in the Libyan jird (<i>Meriones libycus</i>; Rodentia: Muridae) from central Saudi Arabia in the absence of rainfall
Bibliographic record
Abstract
The reproductive pattern of the Libyan jird (Meriones libycus Lichtenstein, 1823) from central Saudi Arabia was investigated in the absence of rainfall. In this study, body mass, morphometry of the reproductive tract, the histology of the reproductive organs, and the hormone concentrations of males and females were studied over 12 consecutive months in a wild population of the Libyan jird from central Saudi Arabia. Previous studies have found the breeding season of the Libyan jird from the Sahara desert of Algeria to occur during the wet months of spring. In the absence of rainfall, temperature and photoperiod were found to be important activators of reproductive activity. The cooler temperatures and shorter days of winter triggered the onset of ovulation in females and increased testes size and seminiferous tubule diameter in males. Only two pregnancies were found during the sampling period, which occurred during the cooler winter and early spring and coincided with a rise in plasma progesterone concentration in females. The Libyan jird was found to shift its breeding to the cooler months of winter in the absence of rainfall. This study strengthens the findings that changes in rainfall and temperature in dry deserts are critical cues for the onset of reproduction in small mammals.
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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) | 0.000 | 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) | 0.000 | 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 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".