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Record W3014139115 · doi:10.17504/protocols.io.29bgh2n

Canopy Trees Survey Protocol - Forests of Southern Québec v1

2019· preprint· en· W3014139115 on OpenAlexaffabout
Mark Vellend, Sabine St‐Jean, Anna L. Crofts

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCanopyDiameter at breast heightForestryTree canopyGeographyForest inventoryDominance (genetics)Crown (dentistry)Environmental scienceRemote sensingCartographyPhysical geographyBiologyForest management

Abstract

fetched live from OpenAlex

Here, we describe the standardized protocol used by the Canadian Airborne Biodiversity Observatory (CABO) to conduct ground-based surveys of canopy trees at forested sites: Parc national du Mont-Mégantic and Mont-Saint-Bruno, Québec. Ground-based canopy tree surveys were conducted in circular sample plots of 15 m radius, with plots distributed across gradients of interest (e.g., species composition, elevation, slope orientation, and logging history), and recorded in the Plots app in Fulcrum. For each sample plot, precise GPS coordinates of plot centres were taken, as well as slope angle and aspect. Within each sample plot, all trees that met the selection criteria were identified to species and geolocated relative to the plot center using the Postex system (Haglöf Sweden AB, Långsele, SE). In addition, height, diameter at breast height (DBH), canopy area, and crown dominance class were estimated for all selected trees. All data were entered into the Vegetation Surveys: Large Trees app in Fulcrum. In Parc national du Mont-Mégantic, for any tree species that had fewer than 10 individuals assigned as 'Dominant' or 'Co-dominant' (crown dominance classes), across all sample plots, additional individuals found outside sample plots were geolocated and measured to bring the sample size to 10 (data recorded in the Plants app in Fulcrum). The ground-based canopy tree surveys were conducted in order to be paired with remotely-sensed aerial hyperspectral imagery.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.115
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1150.017

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 head0.275
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2019
Admission routes2
Has abstractyes

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