Photoperiod effects on the development of beef heifers
Bibliographic record
Abstract
Crossbred beef heifers (n = 144) were assigned at weaning (187 ± 14 d of age) by body weight (225 ± 23 kg) and sire breed (British/Continental) to one of two photoperiod treatments from 21 Decem ber 1998 (0 wk) until 10 May 1999 (20 wk): natural photoperiod (NP) that gradually increased from 8.1 h (0 wk) to 15.2 h (20 wk) and, extended photoperiod (EP) that consisted of natural + supplemental light (400 lx, 1 m above ground) to extend photoperiod to 16 h. Rations were formulated for two-steps of body weight gain (0.6 and 1.2 kg d-1) to achieve 60% of mature weight at 18 wk. Visual observations of estrus behavior were made twice daily and confirmed by serum progesterone. Body weight, backfat and serum prolactin data were determined for each 4-wk period. Ambient temperatures averaged -12.2 ± 6°C in winter (0 to 12 wk) and 4.2 ± 5°C in spring (12 to 20 wk). Gain in body weight was greater (P < 0.05) and backfat lower (P < 0.05) for EP than NP treatments from -2 to 6 wk and only 1% of heifers had attained puberty during this period. However, as yearlings at similar (P > 0.05) body weight and backfat, more (P < 0.05) EP than NP heifers had attained puberty (84.7% vs. 69.4%). Prolactin was greater (P < 0.05) for EP than NP treatments from 2 to 6 wk (10.3 vs 5.5 ± 1.2 ng mL-1). Management of photoperiod influences attainment of puberty and prolactin secretion in beef heifers housed in an outdoor environment. Key words: Photoperiod, puberty, estrus, beef heifers, prolactin
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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) | 0.001 | 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".