Luteal phase length, endometrial edema, and behavior differentiate post‐ovulatory events in a giant panda (<i>Ailuropoda melanoleuca</i>)
Bibliographic record
Abstract
Despite decades of reproductive research on the giant panda (Ailuropoda melanoleuca), the post-ovulatory phase continues to confound zoologists in conservation and breeding centers around the world, often resulting in significant investments of time and resources without reproductive success. The purpose of this project was to document and compare post-ovulatory characteristics during a non-productive and productive breeding in the same individual in consecutive years. A multidisciplinary approach was used to monitor the visiting female giant panda at the Toronto Zoo through the luteal phase of her first two full reproductive cycles in 2014 and 2015. Monitoring occurred via urine-endocrine analysis, weekly ultrasound examinations, and continuous behavioral observations. The 2014 reproductive cycle consisted of a pseudopregnancy, characterized by an extended luteal phase (241 days), the identification of endometrial edema and folding during ultrasound examinations, and a lack of strong association between behavior patterns and urinary progestagen secretion. The 2015 reproductive cycle included increased feeding time through the primary progestagen rise compared to the previous year, followed by simultaneous decrease in appetite and increases in inactivity, resting, sitting upright, and pre-partum-associated behaviors. These changes began 25 days before the birth of twins on Day 153 post-ovulation. Both fetuses were detected via ultrasound 15 days pre-partum. These results suggest that an absence of pre-partum behaviors, ultrasound evidence of endometrial edema without a fetus, and an extended luteal phase may be indicative of pseudopregnancy in giant pandas. Simultaneous monitoring of morphology, behavior, and urinary-endocrine profiles showed clear differences between successful and unsuccessful reproductive years.
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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) | 0.001 | 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".