Black poplar: A model for gene resource conservation in forest ecosystems
Bibliographic record
Abstract
Conservation of genetic resources of forest trees has become a major objective for the management of forests. Much theoretical work has been devoted to the subject, and implementation has already started at the local, national, or international scales. Poplars are probably the most representative and threatened forest tree species of old natural floodplain forests in the temperate zone. Gene conservation needs to be integrated with intensive breeding activities, habitat conservation and restoration. For Populus nigra, while research in genetics and ecology is reinforced, a combined conservation strategy is applied at the European scale; simultaneously, the conservation of riparian ecosystems is also a priority. Research and application benefit from each other. The question now is the evaluation of such an integrated strategy. Criteria and indicators for the follow-up of gene resource management are progressively developed, but still need to be tested on the operational scale. Key words: Populus nigra, poplar, gene resources, in situ conservation, ex situconservation, riparian ecosystem, sustainable management
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".