Vegetation and land use 2009: Monarch Butterfly Biosphere Reserve, Mexico
Bibliographic record
Abstract
Please click here to download the map associated with this article. The Monarch Butterfly Biosphere Reserve in Mexico, with an area of 56,259 hectares, is one of the most important protected natural areas in the world; each year there arrives in its fir forests (Abies religiosa) a remarkable migratory insect, the Monarch butterfly (Danaus plexippus L.), which sets out from southern Canada and the northern USA on a journey of more than 4,000 km. The vegetation and land use of the reserve has been mapped by photo-interpretation of digital aerial photographs from February 2009 with a spatial resolution of 40 cm per pixel. The photographs were printed at a scale of 1:10000 and interpreted using the conventional techniques of photo-interpretation. The plant communities were confirmed by field surveys and digitized on screen, at an average scale 1:5,000, by means of direct comparison of photographic elements within an ortho-corrected mosaic from 2003 and the interpreted photographs from 2009. Classification of the categories of vegetation and land use, both during photo-interpretation and for the composition of the final map legend, was based on the national forest inventory of Mexico, 2000. This method, using digital aerial photographs and combining techniques of photo-interpretation and geographic information systems, has allowed the production of a detailed map.
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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 | 0.002 | 0.002 |
| 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) | 0.017 | 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".