Human sperm vitrification: the state of the art
Bibliographic record
Abstract
Sperm cryopreservation has been widely used in assisted reproductive technology (ART) and has resulted in millions of live births. Two principal approaches have been adopted: conventional (slow) freezing and vitrification. As a traditional technique, slow freezing has been successfully employed and widely used at ART clinics whereas the latter, a process to solidify liquid into an amorphous or glassy state, may become a faster alternative method of sperm cryopreservation with significant benefits in regard to simple equipment and applicability to fertility centers. Sperm vitrification has its own limitations. Firstly, small volume of load is usually plunged to liquid nitrogen to achieve high cooling rate, which makes large volume sample cryopreservation less feasible. Secondly, direct contact with liquid nitrogen increases the potential risk of contamination. Recently, new carriers have been developed to facilitate improved control over the volume and speed, and new strategies have been implemented to minimize the contamination risk. In summary, although sperm vitrification has not yet been applied in routine sperm cryopreservation, its potential as a standard procedure is growing.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".