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Record W6945676294 · doi:10.26071/214b5010-3095-4c61

Characterization of Near-Shore Marine Vegetative Habitat Throughout Fortune Bay and Bay d'Espoir (2023-2025)

2023· dataset· en· W6945676294 on OpenAlexaboutno aff

Bibliographic record

VenueOGSL repository · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBaySeagrassTransectInvertebrateHabitatBaseline (sea)Benthic zoneAbundance (ecology)Marine habitats

Abstract

fetched live from OpenAlex

Characterization of near-shore marine vegetative habitat throughout Fortune Bay and Bay d'Espoir (2023) Data collection began in 2023, on targeted components of coastal ecosystems throughout Fortune Bay, Connaigre Bay and Bay d'Espoir to develop a baseline dataset characterizing seagrass, macroalgae and other habitats created by structure-providing species. This effort will continue through 2027. Throughout ten sites of this region, transect data are collected detailing seagrass and macroalgae species frequency, abundance, and distribution. As part of this characterization, marine sediments are documented along each transect, and in-situ water quality measurements. Additionally, pole seines are conducted at each site to collect baseline data on the presence and diversity of fish and invertebrate species present within these habitats. 1) Seagrass and Macroalgae: Distribution, frequency, and abundance of seagrass and macroalgae are monitored at ten sites. Three transects are surveyed at each site semi-annually to record seasonal growth. 2) Species Inventory: Pole seines are conducted annually at each site to collect baseline data on nearshore fish and invertebrate assemblages. If aquatic invasive species are found during a survey, they are recorded and reported. 3) Marine Sediment: Throughout each transect surveys for seagrass and macroalgae frequency and abundance, estimates of the composition of marine sediment found present and its depth along each transect are recorded at 5 meter intervals. 4) Water Quality: In-situ water quality data is collected at the beginning and end of each transect surveyed. Parameters recorded include dissolved oxygen, pH, salinity, conductivity, temperature and turbidity. 72-hour rainfall and wave conditions of the site at the time of each survey are also recorded. This project is part of the Coastal Environmental Baseline Program Initiative under the Oceans Protection Plan of Fisheries and Oceans Canada.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.738
Threshold uncertainty score0.522

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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