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Record W6926133249 · doi:10.21966/mq9t-bw79

LIDAR Derived Forest Metrics - Calvert Island - British Columbia - Canada

2016· dataset· en· W6926133249 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

VenueHakai Institute · 2016
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsnot available
Fundersnot available
KeywordsLidarCanopyTree canopyVegetation (pathology)Forest ecologyGeographic information systemPoint cloudForest inventory

Abstract

fetched live from OpenAlex

72 LIDAR Derived Forest Metrics - Calvert Island - 20 Meter Spatial Resolution LIDAR forest metrics have been developed for the Calvert Island region. The data are in 20 meter resolution and detail a number of variables about the vegetation layer above the bare earth model. Forest metrics have been grouped to show major statistical themes such as gap fraction, stem height, and density. The information is valuable for classifying forest structure and better understanding ecosystem dynamics. LIDAR Forest Metrics Produced by GWF LiDAR Analytics A full list of derived forest metrics produced by G.W. Frazer is listed at the end of this abstract. LIDAR flights conducted in 2012 and 2014 covered all of Calvert and Hecate Island. Flights were completed in August of 2012 (Terra Remote Sensing) and August of 2014 (Brian Menounos UNBC). Area-based canopy height and density metrics are derived directly from a height-normalized LAS point cloud using proprietary software developed by G.W. Frazer (note: Fusion and LASTools are respectively open-source and commercial software that can be used to extract various area-based canopy metrics). These gridded products (approximately 55 bands) have a user-defined 20 m spatial resolution and include (i) height-based statistics (e.g., min., max., mean, moments, percentiles), (ii) density-based statistics (i.e., gap fraction, canopy cover at fractional and absolute heights above the ground surface), and (iii) diagnostic information (e.g., number of laser points in each cell, number of laser points classified as ground, number of points above a specific height threshold, etc.). Area-based canopy metrics are used to characterize the three-dimensional (3-D) structure of the vegetation canopies. List of LiDAR-Derived Canopy Height, Canopy Density, and Stem Metric Categories: (Based on G.W. Frazer LiDAR Metrics for Calvert / Hecate Island Acquisition 2012 / 2014 metadata document.) Canopy Height Metrics Canopy Density Metrics Percentiles of Laser Canopy Height (LHQ) Bands Canopy Density at Fractional Canopy Heights (CCF) Bands Diagnostic Bands Tree-Top Bands For a full metadata report on LiDAR acquisition please contact data@hakai.org

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.063
Threshold uncertainty score1.000

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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