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Record W4309938229 · doi:10.3390/ani12233271

Cryopreservation of Semen in Domestic Animals: A Review of Current Challenges, Applications, and Prospective Strategies

2022· review· en· W4309938229 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnimals · 2022
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsUniversity of Saskatchewan
FundersMitacs
KeywordsCryopreservationCryoprotectantSemenBiologySpermGermplasmBiotechnologyChemistryCell biologyBotanyEmbryoGenetics

Abstract

fetched live from OpenAlex

Cryopreservation is a way to preserve germplasm with applications in agriculture, biotechnology, and conservation of endangered animals. Cryopreservation has been available for over a century, yet, using current methods, only around 50% of spermatozoa retain their viability after cryopreservation. This loss is associated with damage to different sperm components including the plasma membrane, nucleus, mitochondria, proteins, mRNAs, and microRNAs. To mitigate this damage, conventional strategies use chemical additives that include classical cryoprotectants such as glycerol, as well as antioxidants, fatty acids, sugars, amino acids, and membrane stabilizers. However, clearly current protocols do not prevent all damage. This may be due to the imperfect function of antioxidants and the probable conversion of media components to more toxic forms during cryopreservation.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.892
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.133
GPT teacher head0.410
Teacher spread0.276 · 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