Health and safety of IVF embryos: challenges for the international ET industry
Bibliographic record
Abstract
The current world population is increasing at a fast rate. In order to feed this larger population, food production must increase by 70 percent. Recent reports show a record global production of 58.9 Carcass Equivalent Weight million metric tonnes of beef expected for 2014. It becomes clear that the worldwide agricultural community will have to integrate new technologies to assure the sustainability of global livestock and meat demands. Agriculture has benefited tremendously from the innovation of reproductive technologies such as semen artificial insemination and cryopreservation, embryo transfer and cryopreservation, and in vitro fertilization. Only recently have some developed countries accepted the import and export of frozen IVF embryos and more countries are currently evaluating this. Before 2003, in vitro embryos represented not more than 20% of all embryos produced. After 2003, this jumped to 30 to 39% of all embryos produced, and is increasing. It is clear that South America, and more specifically Brazil, is driving this increase. However, most people in this field would agree that the trend is true for many regions active in this field. International movement of gametes or embryos must be performed in biosecure manners to make certain that pathogenic organisms are controlled and that transmission of infection to recipient animals and progeny is avoided. The embryo transfer industry has adopted appropriate procedures to manage the biosecurity risks and hence mitigate risks of pathogen transmission through international trade of bovine embryos. Techniques for biosecure production of in vivo bovine embryos have been well established. However, as in vitro embryos are relatively new to this business, there are not many papers on the subject of pathogeninteraction with this type of embryo. Certain studies demonstrate that the decontamination of in vitro embryos using recommended procedures is effective for specific pathogens while others have shown that this is not as evident in other conditions. All agree that more research is needed regarding washing protocols for in vitro embryos. It is imperative that the scientific community continues its research to validate current embryo sanitary washing procedures and recommend any modifications that would be necessary for IVF embryos. As embryos are becoming an important component of international trade of bovine genetics, such research must not only continue but augment if key parties want to assure they meet the worldwide rising need of meat and dairy products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".