MétaCan
Menu
← Back to cohort
Record W3015213315 · doi:10.17504/protocols.io.9zch72w

Small Drone Photos - Open Vegetation Protocol v1

2019· preprint· en· W3015213315 on OpenAlexaffabout
Sabine St‐Jean, Étienne Laliberté

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsDroneVegetation (pathology)GeographyBogBiodiversityAbundance (ecology)ObservatoryProtocol (science)ForestryCamera trapCartographyPhysical geographyRemote sensingEcologyHabitatArchaeologyBiologyAstronomyPhysics

Abstract

fetched live from OpenAlex

Here we describe the standardised protocol used by the Canadian Airborne Biodiversity Observatory (CABO) to take small drone pictures of the plots and subplots in open vegetation surveys. In 2019, such pictures were taken at the Mer Bleue Bog (Ontario) and Parc national des Îles-de-Boucherville (Québec) sites. These pictures are to be classified later (see the Post Processing protocol) to obtain the abundance and distribution of plant species through every subplot.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.412
Threshold uncertainty score0.839

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4120.181

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 head0.088
GPT teacher head0.315
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

Same topicSpecies Distribution and Climate Change→French-language works237,207→