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Record W2556899291 · doi:10.21451/1984-3143-ar907

Intrinsic and extrinsic factors that influence ovarian environment and efficiency of reproduction in cattle

2016· article· en· W2556899291 on OpenAlexfundno aff
Pietro Sampaio Baruselli, E. O. S. Batista, Leandro M. Vieira, J. N. S. Sales, Lindsay Unno Gimenes, R. M. Ferreira

Bibliographic record

VenueAnimal Reproduction · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
FundersCarraresi FoundationEuropean Foundation for the Study of DiabetesUniversità degli Studi di Milano
KeywordsReproductionBiologyInternal medicineEndocrinologyMedicineEcology

Abstract

fetched live from OpenAlex

All the somatic cells composing a mammalian organism are genetically identical and contain the same DNA sequence. Nevertheless, they are able to adopt a distinct commitment, differentiate in a tissue specific way and respond to developmental cues, acquiring a terminal phenotype. At the end of the differentiation process, each cell is highly specialized and committed to a distinct determined fate. This is possible thanks to tissue-specific gene expression, timely regulated by epigenetic modifications, that gradually limit cell potency to a more restricted phenotype-related expression pattern. Complex chemical modifications of DNA, RNA and associated proteins, that determine activation or silencing of certain genes are responsible for the 'epigenetic control' that triggers the restriction of cell pluripotency, with the acquisition of the phenotypic definition and the preservation of its stability during subsequent cell divisions. The process is however reversible and may be modified by biochemical and biological manipulation, leading to the reactivation of hypermethylated pluripotency genes and inducing cells to transit from a terminally committed state to a higher plasticity one.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.227

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 head0.021
GPT teacher head0.218
Teacher spread0.197 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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