MétaCan
Menu
Back to cohort
Record W2970017019 · doi:10.1177/1091581819867929

Biochemical and Electroretinographic Characterization of the Minipig Eye in the Context of Drug Safety Investigations

2019· article· en· W2970017019 on OpenAlexaff
Luis Fernando Negro Silva, Christian Li, Paula Juliana Brizuela de Seadi Pereira, Wendy Tan, Michelle Dubuc-Mageau, Audrey Sanfacon, Roy Forster, Robert Tavcar, Andy Makin, Simon Authier

Bibliographic record

VenueInternational Journal of Toxicology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsElectroretinographyMedicineErgContext (archaeology)OphthalmologyPharmacologyRetinalBiology

Abstract

fetched live from OpenAlex

Minipigs are an emerging nonrodent alternative for ocular toxicology owing to anatomical similarities in the minipig eyes when compared to humans. Ocular structures and components from Göttingen minipigs were characterized and compared to species commonly used in toxicology. Ocular reference data from Göttingen minipig including intraocular pressure, vitreous electrolyte and thiol concentration, and electroretinography (ERG) data are essential to model characterization and data interpretation during drug safety assessments. Intravitreal positive control agents including gentamicin, indocyanine green, and glycine were used to demonstrate ERG alterations caused by retinal cell toxicity, light transmission obstruction, or neurotransmission interferences, respectively. Electrolyte concentrations of the aqueous and vitreous humors from Göttingen minipigs were similar to other species including humans. The reference data presented herein supports the use of the Göttingen minipig as an alternate nonrodent species in ocular toxicology.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.233
Teacher spread0.228 · 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 designBench or experimental
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

Citations8
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of ToxicologySame topicRetinal Development and DisordersFrench-language works237,207