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Record W6940812626 · doi:10.11575/prism/41453

Identifying research gaps regarding the influence of maternal stress on bovine female offspring’s Anti-Müllerian hormone (AMH) concentrations: A scoping review protocol

2023· other· en· W6940812626 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2023
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCullingFertilityAntral follicleInfertilityBeef cattleLongevityPopulationFollicular phasePregnancy

Abstract

fetched live from OpenAlex

Introduction: Farmers consistently aim to increase cattle longevity in their herds to improve sustainability of cattle production. However, infertility or low fertility is one of the reasons for culling healthy dairy and beef cows with a negative impact on longevity. In dairy cattle, around 14.2% in Canada and 26.7% in the U.S. (CDIC, 2022; USDA, 1996) of cattle are culled due to fertility issues, with a similar percentage for beef cattle (US, 27.2%; USDA, 1999). Fertility in these animals shows a progressive decline which points to a long-term effect that could start during ovarian development (Wathes et al., 2014 ). The ovaries in cattle develop in utero (30-90 d of pregnancy) with heifers having their lifetime supply of follicles at birth (i.e., ovarian reserve, OR; Hernandez-Medrano et al., 2012). Any disruption in the development of the OR may result in fertility complications and decreased reproductive longevity (Hernandez-Medrano et al., 2012; Mossa et al., 2015; Akbarinejad et al., 2017). Maternal stress, such as thermal or nutritional, are some of those disruptions that have a long-lasting effect on offspring health and productive potential. The exact mechanisms for these effects are still elusive. Growing follicles produce the dimeric glycoprotein hormone, Anti-Müllerian hormone (AMH), which has been reported as a marker for the antral follicular population in cows and their reproductive potential (Alward & Bohlen, 2019). This review will identify publications that have studied the link between maternal stress and gonadal development, ultimately resulting in a breakdown of what’s known regarding the influence of maternal stress during gestation on AMH concentrations in female offspring. Objective: The objective of this review is to identify the published literature discussing how AMH concentrations in bovine female offspring are influenced by nutritional or thermal stress experienced by the dam during gestation. The results will highlight areas of consensus and propose research approaches to fill the gaps in knowledge. The overall goal of this scoping review is to evaluate the feasibility to implement AMH as an early marker of reproductive potential and help producers improve the sustainability of their farms. Methods: A scoping review reported according to the PRISMA scoping review extension will be carried out with a total of five databases being used for the study (CAB Abstracts, MEDLINE, BIOSIS Previews, the Web of Science, and SciELO). Concepts to be considered in the primary search include cattle, pregnancy, nutritional or thermal stress, and offspring outcomes. Article screening will consist of two stages: title and abstract, and full text. Articles will be included in the review if they discuss AMH concentrations, bovine female offspring, and are peer-reviewed academic journal articles or conference proceedings. Articles will then be excluded from the study if they are non-English or non-Spanish. The articles that meet this criterion will then be charted in an Excel spreadsheet.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.038
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.062
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.011
Bibliometrics0.0190.011
Science and technology studies0.0030.002
Scholarly communication0.0060.005
Open science0.0030.005
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0220.003

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 head0.108
GPT teacher head0.397
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2023
Admission routes1
Has abstractyes

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