Bibliographic record
Abstract
with six regional offices located in Asia, Africa and Latin America, is a public corporation established by the Parliament of Canada in 1970. The Centre was created to help communities in the developing world find practical solutions to the social, economic, and environmental problems they face. Support is directed toward broadening local knowledge and capacity to enable communities to build healthier, more equitable, and more prosper societies. In doing so, IDRC also strengthens the overall capability of research institutions to generate policies and technologies that can help create more equitable societies. The Government of Canada finances IDRC;its policies are however set by an international Board of Governors. MAP PA The Medicinal and Aromatic Plants Program in Asia (MAPPA) is a program of strategic research, networking and collaboration to comprehensively address critical research issues related to the sustainable and equitable use of medicinal and aromatic plants in Asia. Mappa is a joint initiative of IDRC, IFAD and the Ford Foundation. Through collaboration and partnerships, and based within a regional approach to theseissues, MAPPA is involved in formulating and implementing a holistic program which will complementand build on other related research and development activities in South Asia. This will be achieved by supporting strategic research, building partnerships among the key stakeholders including
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.009 |
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".