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Record W2012116092 · doi:10.1080/01431160500075857

Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer

2005· article· en· W2012116092 on OpenAlexafffundabout
Jim Gower, Stephanie King, Gary A. Borstad, Leslie Brown

Bibliographic record

VenueInternational Journal of Remote Sensing · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsFisheries and Oceans Canada
FundersFisheries and Oceans CanadaCanadian Space AgencyEuropean Space AgencyAustralian Government
KeywordsRadianceImaging spectrometerRemote sensingEnvironmental scienceSatelliteSpectrometerOcean colorOceanographyGeologyPhysicsOpticsAstronomy

Abstract

fetched live from OpenAlex

Intense plankton blooms (colloquially called ‘red tides’) are becoming an increasingly important phenomenon in coastal waters. This Letter shows how the European satellite sensor MERIS (Medium Resolution Imaging Spectrometer) can be used to detect a peak in the optical spectrum of water‐leaving radiance near 705 nm which provides a more specific response to some types of these blooms. Images and spectra are presented, derived from a MERIS scene where small areas have this response. One such area is at the site of a fish farm where bloom conditions were confirmed by surface observations and measurements. The observed spectra are compared to model results to demonstrate how these responses arise. Inspection of data from other parts of the world shows similar features in US and European waters.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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
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

Citations345
Published2005
Admission routes3
Has abstractyes

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