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Plasma melatonin and insulin‐like growth factor‐1 responses to dim light at night in dairy heifers

2006· article· en· W2156878791 on OpenAlexafffund
P. Muthuramalingam, A. D. Kennedy, R. J. Berry

Bibliographic record

VenueJournal of Pineal Research · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Manitoba
FundersManitoba Hydro
KeywordsMelatoninRadioimmunoassayEndocrinologyInternal medicineLatin squareInsulin-like growth factorDarknessPlasma levelsAnimal scienceCircadian rhythmphotoperiodismInsulinBiologyChemistryGrowth factorMedicineBiochemistry

Abstract

fetched live from OpenAlex

The effect of dim (5, 10 and 50 1x) light at night on night plasma melatonin level (NML) and night plasma insulin-like growth factor-1 (IGF-1) level was determined in 12 prepubertal Holstein heifers (245 +/- 16 days age) using a 4 x 4 Latin Square design with 14-day treatment and 14-day recovery periods. Blood samples were collected at 23:00 hr (prior to the 8 hr night treatment which commenced at mid-night) on days 0, 3 and 13, and throughout the night at 01:00, 02:00, 03:00, 04:00, 06:00 and 08:00 hr on days 1, 4 and 14 of treatment. Plasma was analysed by radioimmunoassay for melatonin (all samples) and IGF-1 (samples for day 14, 04:00 hr only). Treatment (P = 0.03) and treatment x time (P = 0.02) were significant for NML. Exposure to 50 lx suppressed NML by 50% during the initial 2 hr of the night, but not thereafter. Exposure to 5 and 10 lx had no effect on NML. The NML response to 50 lx was found on all treatment days studied (treatment x time x day; P = 0.99). There was no treatment effect on plasma IGF-1 level (P = 0.89), but plasma IGF-1 level was higher (P = 0.001) during period 4. Plasma IGF-1 level and NML tended (P = 0.10) to be negatively correlated. Light intensities of 10 lx or less appear safe for use at night in dairy barns where darkness is recommended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.324
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2006
Admission routes2
Has abstractyes

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