Best practices in the use and exchange of microorganism biological control genetic resources
Bibliographic record
Abstract
Abstract The Nagoya Protocol actions the third objective of the Convention on Biological Diversity and provides a framework to effectively implement the fair and equitable sharing of benefits arising out of the use of genetic resources. This includes microorganisms used as biological control agents. Thus biological control practitioners must comply with access and benefit-sharing regulations that are implemented by countries providing microbial biological control agents. A review of best practices and guidance for the use and exchange of microorganisms used for biological control has been prepared by the IOBC Global Commission on Biological Control and Access and Benefit-Sharing to demonstrate commitment to comply with access and benefit-sharing requirements, and to reassure the international community that biological control is a very successful and environmentally safe pest management strategy that uses biological resources responsibly and sustainably. We propose that best practices include the following elements: collaboration to facilitate information exchange about the availability of microbial biological control agents and where they may be sourced; freely sharing available knowledge in databases about successes and failures; collaborative research with provider countries to develop capacity; and production technology transfer to provide economic opportunities. We recommend the use of model concept agreements for accessing microorganisms for scientific research and non-commercial release into nature where access and benefit-sharing regulations exist and where regulations are not restrictive or do not exist. We also recommend a model agreement for deposition of microbial biological control agents into culture collections.
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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 | 0.160 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.009 | 0.006 |
| 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".