How free access internet resources benefit biodiversity and conservation research: Trinidad and Tobago's endemic plants and their conservation status
Bibliographic record
Abstract
Abstract Botanists have been urged to help assess the conservation status of all known plant species. For resource-poor and biodiversity-rich countries such assessments are scarce because of a lack of, and access to, information. However, the wide range of biodiversity and geographical resources that are now freely available on the internet, together with local herbarium data, can provide sufficient information to assess the conservation status of plants. Such resources were used to review the vascular plant species endemic to Trinidad and Tobago and to assess their conservation status. Fifty-nine species were found to be endemic, much lower than previously stated. Using the IUCN Red List criteria 18 endemic species were assessed as Critically Endangered, 16 as Endangered, 15 as Vulnerable, three as Near Threatened, and three as Data Deficient (i.e. insufficient data are available to assess their conservation status). Although such rapid assessments cannot replace in depth research, they provide essential baseline information to target research and conservation priorities and identify specific conservation actions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".