Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When most people hear the word Madagascar, images of animated dancing lemurs and quirky stranded penguins come to their minds. Although there is some truth in the movie’s description of that far-away, mysterious place, it fails to paint a complete picture of Madagascar as being rich in biodiversity and culture. Few places on earth rival the variety of endemic plants and animals that are found there. It is estimated that Madagascar has more genetic diversity per unit area than anywhere else on earth (Karsten, et al., 2009). This makes it “one of the world’s hottest hotspots for biodiversity conservation” (Consiglio, et al., 2006). Even though Madagascar is a biologically invaluable nation, it trails behind other ecologically notable countries, like Ecuador, in the conservation effort. Madagascar continues to suffer devastating loss to its precious habitats. The Madagascar government has the difficult task of preserving as much ecologically unique territory as it can, without depriving the already economically disadvantaged local people. Much international help is needed in providing support to the people and protection to the plants, animals, and natural resources of Madagascar.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it