Core body temperature monitoring with passive transponder boluses in beef heifers
Bibliographic record
Abstract
Experiments were conducted over 82 d (Nov. 04 to Jan. 24, 49°N, mean ambient temperature -3.6 to -12.6 ± 1.6°C) to determine the effects of fever, photoperiod and pen setup on the rate (MR) and frequency (MF) with which heifers were monitored and the body (rumen) temperatures (BTr) obtained with a cattle temperature moniotoring system (MaGiiX). Magnetic, inductively coupled full duplex radio-frequency identification (RFID) transponder boluses containing thermistors were administered per os to 72 heifers (7.9 ± 0.5 mo of age and 283 ± 23 kg body weight) housed in one of four pens, in outdoor shed-lot facilities, each with a panel reader co-located with the waterbowl. A mixed ration (59% dry matter) was provided at 1500 daily. Fencing was arranged within pens for water motivated (WM) acquisitions during exps. 1 (Initial), 2 (Fever) and 3 (Photoperiod), or for either WM or activity motivated (AM) acquisitions during exp. 4 (Pen setup). Overall, most heifers were monitored daily (Mode MR 100%), several times perday (MF 7.8 ± 0.5), mostly during the afternoon and evening rather than night and morning 6-h periods, and BTr (37.8 ± 0.2°C, range 22 to 42°C) were usually lower (P < 0.05) for the afternoon than night. A 2°C increase in mean BTr caused by fever was detected (P < 0.05) when monitoring was scheduled rather than unscheduled. Extended (16h) in contrast to natural (8h) photoperiod increased (P < 0.05) evening MR (96.8 vs.83.5 ± 1.9%) and MF (3.8 vs. 2.5 ± 0.2), and morning-BTr (38.0 vs. 37.4 ± 0.11°C). Pen setup for AM in contrast to WM acquisitions increased (P < 0.05) MR and MF and BTr (by 1°C) in all periods of the day. The technology has excellent potential for non-invasive monitoring of BTr in heifers. Key words: Radio-frequency identification, cattle, transponder bolus, body temperature, rumen
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".