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Record W6894523145 · doi:10.5683/sp3/cehucp

Effects of lysine and methionine on mRNA expression of candidate transcription factors by primary bovine mammary epithelial cells

2024· dataset· en· W6894523145 on OpenAlexaff

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsMcGill UniversityUniversity of Guelph
Fundersnot available
KeywordsLysineMethionineMessenger RNAEndoplasmic reticulumTranscription factorAmino acidGene expressionTranscription (linguistics)

Abstract

fetched live from OpenAlex

The dataset originates from an experiment investigating the effects of lysine and methionine on mRNA expression of candidate transcription factors in primary bovine mammary epithelial cells. The objective of this study is evaluate if and when the candidate gene expression in bovine mammary epithelial cell is affected after imposing an essential amino acid deficiency in vitro, and to evaluate effects of essential amino acid deficiency on protein synthesis, endoplasmic reticulum size, cell proliferation and lipogenesis.

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0110.013

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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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Same venueBorealisFrench-language works237,207