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Record W4405632118 · doi:10.7213/acad.2024.22009

Protein quantification in frozen swine semen filtered with Percoll

2024· article· en· W4405632118 on OpenAlexaff
Manuel Barrientos-Morales, Claudia Karina Lagunes-Moreno, M. Á. López, Ivan Avalos-Rosario, Izabella Witelus, Sandra Elena Montaño García

Bibliographic record

VenueRevista Acadêmica Ciência Animal · 2024
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPercollSemenChromatographyChemistryDilutionAbsorbanceCryopreservationCentrifugationBiologyAnatomy

Abstract

fetched live from OpenAlex

In this study, the protein concentration in fresh and frozen semen samples from three breeds was determined using discontinuous Percoll gradients. Ejaculates (n = 34) from Large White, German Pietrain, and Duroc-Jersey boars were cryopreserved. After thawing, Percoll gradients were used to process the samples. Protein extraction was performed through the Bradford method. The absorbance of the solution was measured using a microplate spectrophotometer at 562 nm and aliquots were analyzed after solvation. Protein concentration were evaluated using the absorbance values of the lowest dilution within the calibration range. Protein concentration was higher in fresh samples (0,169 mg/ml) compared to frozen samples (0,127 mg/ml). Among breeds, Duroc samples showed the highest protein concentration (0,163 mg/mL), followed by Large White (0,146 mg/mL), and German Pietrain (0,129 mg/mL). Therefore, it was shown that cryopreservation caused a decrease in protein concentration.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.269
Teacher spread0.250 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueRevista Acadêmica Ciência AnimalSame topicSperm and Testicular FunctionFrench-language works237,207