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Record W1976708687 · doi:10.4113/jom.2010.1123

Vegetation and land use 2009: Monarch Butterfly Biosphere Reserve, Mexico

2010· article· en· W1976708687 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Maps · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsMonarch butterflyGeographyButterflyDanausVegetation (pathology)BiosphereAerial photosCartographyAerial photographyAmazon rainforestForestryScale (ratio)MosaicRemote sensingArchaeologyPhysical geographyEcology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.023
GPT teacher head0.248
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it