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Record W2272069165 · doi:10.5065/d6319svb

Nutrients, Chlorophyll, Primary Production and Realted Biogeochemical Properties in the Ocean Mixed Layer / a Compliation of Data Collected at Nine JGOFS Sites

2001· article· en· W2272069165 on OpenAlexaboutno aff
A. Kleypas, C. Doney

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsBiogeochemical cycleEnvironmental scienceNutrientOceanographyMixed layerPrimary productionChlorophyll aPrimary productivityPrimary producersPhytoplanktonEcosystemGeologyEnvironmental chemistryEcologyChemistryBiologyBotany

Abstract

fetched live from OpenAlex

This technical report provides summary data for nine distinct US JGOFS and international JGOFS sites. Four of these are point-locations where long-term time-series data have been collected: the Bermuda Atlantic Time-series Study (BATS); the Hawaiian Ocean Timeseries (HOT); KERFIX, the French JGOFS site; and Station P, the Canadian JGOFS time-series station. The remaining sites are U.S. JGOFS Process Study sites: Arabian Sea; Equatorial Pacific (EqPac); North Atlantic Bloom Experiment (NABE); and the Antarctic Environment and Southern Ocean Survey (AESOPS) (which includes two distinct regions: the Ross Set and Antarctic Polar Front Zone). To provide an easy to use, practical presentation of data from each of these sites, both depth-profile data and the mixed layer average for each variable are determined on a cast-by-cast basis. Where possible, data are also standardized to common units. These data are available through the Data Support Section of the National Center for Atmospheric Research (http://dss.ucar.edu/datasets/) as dataset 259.0.

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)0.001
metaresearch head score (Gemma)0.002
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: Dataset
Teacher disagreement score0.095
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.006
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.003

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 head0.051
GPT teacher head0.217
Teacher spread0.166 · 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

Citations13
Published2001
Admission routes1
Has abstractyes

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