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Record W2592437294 · doi:10.1017/s0967199417000016

Comparison of different extenders on the recovery and longevity of epididymal sperm from Spix's yellow-toothed cavies (<i>Galea spixii</i> Wagler, 1831)

2017· article· en· W2592437294 on OpenAlexfundno aff
Andréia Maria da Silva, Patrícia C. Sousa, Lívia Batista Campos, José Artur Brilhante Bezerra, Arthur Emannuel de Araújo Lago, Moacir Franco de Oliveira, Alexandre Rodrigues Silva

Bibliographic record

VenueZygote · 2017
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversidade Federal Rural do Semi-ÁridoEgg Farmers of Canada
KeywordsSpermGaleaEpididymisDiluentTrisAndrologyChemistryIncubationBiologyAnatomyMedicineBiochemistryNuclear chemistry

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the performance of cavy (Galea spixii) epididymal sperm following addition to TES or TRIS extenders and using a thermal resistance test (TRT), as well as fluorescence analysis as a complementary method to predict the viability of these gametes. Nine testicle-epididymis complexes were used for sperm collection using a flotation method. Epididymis tails were sliced and one was immersed in 3 ml of TRIS buffer, and the other in 3 ml of TES, for 5 min. After sperm recovery, the samples were subjected to a TRT which involved incubation in a water bath at 37°C for 3 h. During incubation, sample parameters were assessed at 0, 15, 30, 60, 90, 120, 150 or 180 min intervals. Results indicated that the TRIS diluent was more efficient than TES (P < 0.05) for the maintenance of sperm parameters in Spix's yellow-toothed cavies over the whole TRT, maintaining sperm longevity for an extended time. In conclusion, we indicate the use of TRIS diluent for recovery and maintenance of longevity of epididymal sperm from cavies (G. spixii).

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.058
GPT teacher head0.317
Teacher spread0.259 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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