MétaCan
Menu
Back to cohort
Record W6892014440 · doi:10.48579/pro/9si1pn

Vegetation surveys in mountainous area (Pyrenees, France)

2022· dataset· en· W6892014440 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuedata.InDoRES · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsVegetation (pathology)Cover (algebra)Vegetation coverRaw dataLand coverScale (ratio)Data fileSnow cover

Abstract

fetched live from OpenAlex

The data file contains absolute cover percentage of plant species from vegetation survey in the Vicdessos mountainous area (Pyrenees, France). The data have been collected in 2015 and 2020 within the framework of two projects: ANR-10-JCJC-1804 MODE-RESPYR (Modeling Past and future land cover changes in the Pyrenees) and the PASTSERV project funded by the Observatoire Hommes-Milieux Pyrenees Haut Vicdessos (Labex DRIIHM ANR-11-LABX0010). All observed vascular plant species were listed and the cover of each species was estimated using the seven degrees of the Braun-Blanquet scale (r, +, 1, 2, 3, 4, 5). These codes were then converted to absolute percentage cover (van der Maarel 1979). The version of the data file formatted according to the Darwin Core standard has been uploaded to GBIF (https://doi.org/10.15468/4q47d3). This file is the original raw data file.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.028
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0050.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.005

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 head0.041
GPT teacher head0.298
Teacher spread0.257 · 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

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuedata.InDoRESFrench-language works237,207