Melatonin and cashmere growth in Inner Mongolian cashmere goats
Bibliographic record
Abstract
The aim of the study was to investigate the effects of melatonin implants on cashmere growth and productive performance of cashmere goats. A total of thirty female goats were assigned to one of three treatments (n = 10), including control and two treatments where melatonin [2 mg kg−1 body weight (BW)] was implanted either in April and June or in June. Compared with the control, implantation in April and June increased cashmere yield and maximum cashmere length by 20.3% and 15.7%, respectively (P < 0.01), with an average initiation date of 22 May 2013 and cessation date of 26 Mar. 2014. In contrast, no cashmere growth was observed in control goats until 19 June 2013 and the growth ceased on 3 Apr. 2014. Melatonin only implanted in June had no effect on cashmere yield and maximum cashmere length, with an average initiation date of 5 June 2013 and cessation date of 27 Mar. 2014. Cashmere growth rate, cashmere fiber diameter, the final BW, and average daily gain were not influenced by melatonin implantation. Results suggested that melatonin implantation during the cashmere nongrowing period is an effective way to stimulate cashmere growth and extend the cashmere growth phase with April and June identified as the most appropriate time for implantation.
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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 | 0.000 | 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".