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Record W6945360772 · doi:10.21966/x3jm-p494

Eelgrass (Z. marina) extent at Gulf Islands National Park Reserve eelgrass monitoring sites (2024)

2024· dataset· en· W6945360772 on OpenAlexaffabout

Bibliographic record

VenueHakai Institute · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsParks Canada
Fundersnot available
KeywordsZostera marinaNational parkCitizen scienceGeoreferenceAerial surveyAerial photographyGeographic information systemNature tourismTourismGNSS applications

Abstract

fetched live from OpenAlex

This data package contains the datasets and reports pertaining to mapping the spatial extent of Zostera marina at several monitoring sites within the Gulf Islands National Park Reserve, British Columbia, Canada. This work was a collaborative project between the Hakai Institute and the Gulf Islands National Park Reserve (GINPR). Four eelgrass monitoring sites were mapped in partnership with the Hakai Institute and Gulf Islands National Park Reserve in 2024. Three eelgrass monitoring sites (James Bay, Tumbo, Cabbage) were mapped using small Remotely Piloted Aerial Systems (RPAS), and a fourth site, Sidney Spit, was mapped by the Hakai Aerial Coastal Observatory (ACO) - a fixed-wing aircraft with two medium format cameras (RGB and NIR). Orthomosaics of each site were generated using a Structure from Motion Multi-View Stereo (SfM-MVS) workflow in Agisoft Metashape (Version 2.1.61, Pix4D) in Windows 10. Orthomosaics were georeferenced to either previous surveys (James Bay, Cabbage, Tumbo) or using post-processed GNSS data with onboard IMU data in the case of the ACO survey. The extent of eelgrass at each site was delineated using object-based image analysis (OBIA) with eCognition Developer software (eCognition Developer 10.1, 2014) and manual delineation (where necessary). Georeferenced towed underwater video (SplashCam Pro) data were collected at eelgrass monitoring sites to provide ground-truth data for verifying eelgrass extent. The data package includes: - The report (.pdf) which describe the project, data collection, processing methods and results for the 2024 surveys. Comparison to previous eelgrass surveys is also included. - A report (.pdf) which describes the Aerial Coastal Observatory (ACO) survey methods and equipment. - Polygon shapefiles (.shp) of the extent of eelgrass (Z. marina) at each monitoring site. - Point shapefiles (.shp) of classified towed underwater video transects*. - A data dictionary (.csv) which describes the attributes of the eelgrass and towed video shapefiles. - For Sidney Spit - field photos and transect surveys of eelgrass and green algae are provided as shapefiles. *The towed underwater video footage is not available. This data package is a component of the Hakai Institute’s Habitat Mapping program whose overarching objective is to generate spatial inventories of coastal habitats, investigate how these habitats are changing through time and the drivers of that change. These data were collected as a part of the Coastal BC Nearshore Habitat Mapping Project (a collaboration between Parks Canada and the Hakai Institute). Permission to use this dataset must be granted by the Hakai Institute and Gulf Islands National Park Reserve to the individual who makes the data request.

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 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), 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 score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.012

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 head0.032
GPT teacher head0.257
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes2
Has abstractyes

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