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Record W1976323599 · doi:10.1029/2005jc002880

A two‐component model of phytoplankton absorption in the open ocean: Theory and applications

2006· article· en· W1976323599 on OpenAlexaff
Emmanuel Devred, Shubha Sathyendranath, Venetia Stuart, Heidi Maass, Osvaldo Ulloa, T. Platt

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsBedford Institute of OceanographyDalhousie University
FundersComisión Nacional de Investigación Científica y Tecnológica
KeywordsPhytoplanktonAbsorption (acoustics)OceanographyChlorophyll aPopulationEnvironmental scienceAttenuation coefficientAtmospheric sciencesBiologyEcologyPhysicsGeologyBotanyOpticsNutrient

Abstract

fetched live from OpenAlex

The two‐population absorption model of Sathyendranath et al. is extended to retrieve the specific absorption coefficients (absorption per unit concentration of chlorophyll‐ a ) of the component populations of phytoplankton. The model relates the absorption coefficient of phytoplankton to chlorophyll‐ a concentration, assuming that the assemblages of phytoplankton comprise mixtures of two populations whose proportions vary as the total concentration of cells changes. The model is applied to in situ data collected from six regions during 34 cruises. The model compares well with earlier models of phytoplankton absorption but brings the additional advantage of parameters that have clear bio‐optical and biological interpretation. Size structure of the phytoplankton populations was inferred from the values of the specific absorption coefficients. The results are consistent with pigment analyses performed on the same samples. Seasonal analysis of data from the northwest Atlantic, southeast Pacific, and the Arabian Sea showed significant changes in the spectral form and magnitude of the specific absorption coefficients of small‐ and large‐celled populations, which appear to be related to changes in species composition. The model serves thus as an optical tool to explore the large‐scale biogeography of phytoplankton.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.322
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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 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

Citations164
Published2006
Admission routes1
Has abstractyes

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