Cryobanking of viable biomaterials: implementation of new strategies for conservation purposes
Bibliographic record
Abstract
Cryobanking, the freezing of biological specimens to maintain their integrity for a variety of anticipated and unanticipated uses, offers unique opportunities to advance the basic knowledge of biological systems and their evolution. Notably, cryobanking provides a crucial opportunity to support conservation efforts for endangered species. Historically, cryobanking has been developed mostly in response to human economic and medical needs - these needs must now be extended to biodiversity conservation. Reproduction technologies utilizing cryobanked gametes, embryos and somatic cells are already vital components of endangered species recovery efforts. Advances in modern biological research (e.g. stem cell research, genomics and proteomics) are already drawing heavily on cryobanked specimens, and future needs are anticipated to be immense. The challenges of developing and applying cryobanking for a broader diversity of species were addressed at an international conference held at Trier University (Germany) in June 2008. However, the magnitude of the potential benefits of cryobanking stood in stark contrast to the lack of substantial resources available for this area of strategic interest for biological science - and society at large. The meeting at Trier established a foundation for a strong global incentive to cryobank threatened species. The establishment of an Amphibian Ark cryobanking programme offers the first opportunity for global cooperation to achieve the cryobanking of the threatened species from an entire vertebrate class.
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 | 0.000 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".