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Record W2735319567 · doi:10.22621/cfn.v131i1.1783

Inexpensive Video Drop-camera for Surveying Sensitive Benthic Habitats: Applications from Glass Sponge (Hexactinellida) Reefs in Howe Sound, British Columbia

2017· article· en· W2735319567 on OpenAlexfundvenueaboutno aff
Lena Clayton, Glen Dennison

Bibliographic record

VenueThe Canadian Field-Naturalist · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsBathymetrySound (geography)ReefOceanographySide-scan sonarBenthic zoneGeologyFishingFisheryEnvironmental scienceRemote sensingSonar

Abstract

fetched live from OpenAlex

Where marine waters are shallow and bathymetric features are steep, the typically employed multi-beam side scan sonar is not always reliable for identifying complex biological structures. Here, we present a cost-efficient method used in Howe Sound, British Columbia, for bathymetric mapping, exploration, and ground-truthing of glass sponge bioherms. A simple depth sounder and software package was used to produce bathymetric maps. From these maps, prospective sites were selected and surveyed to investigate bioherm presence with a simple drop-camera towed off the bow of a small drifting vessel during calm seas. This method was used during a 4-year citizen science initiative that led to the discovery of 12 glass sponge bioherms in Howe Sound, the first step in protecting these globally unique reefs from the impact of bottom-contact fishing, anchoring, and potential industrial contamination. Before our work using this method, only two glass sponge bioherms had been identified in Howe Sound. The method also proved effective as a means to quantify damage to bioherms from fishing gear.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations7
Published2017
Admission routes3
Has abstractyes

Explore more

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