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Record W2102555522 · doi:10.1029/2007eo110003

Developing standards for dissolved iron in seawater

2007· article· en· W2102555522 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEos · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSeawaterPhytoplanktonIron fertilizationEnvironmental scienceOceanographyEnvironmental chemistryChemistryNutrientGeology

Abstract

fetched live from OpenAlex

In nearly a dozen open‐ocean fertilization experiments conducted by more than 100 researchers from nearly 20 countries, adding iron at the sea surface has led to distinct increases in photosynthesis rates and biomass. These experiments confirmed the hypothesis proposed by the late John Martin [ Martin , 1990] that dissolved iron concentration is a key variable that controls phytoplankton processes in ocean surface waters However, the measurement of dissolved iron concentration in seawater remains a difficult task [ Bruland and Rue , 2001] with significant interlaboratory differences apparent at times. The availability of a seawater reference solution with well‐known dissolved iron (Fe) concentrations similar to open‐ocean values, which could be used for the calibration of equipment or other tasks, would greatly alleviate these problems [ National Research Council (NRC) , 2002[.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.249
Teacher spread0.233 · 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