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Record W2515299956 · doi:10.1071/rd16164

Testicular parameters and spermatogenesis in different birthweight boars

2016· article· en· W2515299956 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReproduction Fertility and Development · 2016
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsAdidas (Canada)
FundersBiotechnology and Biological Sciences Research Council
KeywordsSpermatogenesisLitterBiologySpermSomatic cellAndrologyTestosterone (patch)SemenAnimal scienceEndocrinologyMedicineGeneAnatomyGeneticsEcology

Abstract

fetched live from OpenAlex

The present study investigated the effect of birthweight on testicular development and spermatogenesis in boars. Twenty-four pairs of littermate boars were selected: one piglet with the highest birthweight (HW) and the other with the lowest birthweight (LW) within the litter. Two subsets of 12 pairs of male littermates from each birthweight group were obtained after selection: one subset was orchiectomised at 8 days and the other at 8 months of age. HW boars had higher body and testicular weights at both ages (P<0.05). Testosterone concentrations and the relative expression of 17α-hydroxylase in the testis were similar between birthweight groups. Birthweight affected somatic and germ cell numbers in the neonatal testis, which were higher in HW boars (P<0.05). Moreover, a significant reduction in the number of pachytene spermatocytes and round spermatids was observed in LW boars (P<0.05) at 8 months of age, which caused a decrease in the total number of elongated spermatids and daily sperm production (P<0.05). Hence, HW boars have the potential to produce more spermatozoa and consequently more semen doses per ejaculate, and would be very valuable to an industry that relies on AI.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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