MétaCan
Menu
Back to cohort
Record W1592742956 · doi:10.1029/2005gb002481

Acquisition of iron bound to strong organic complexes, with different Fe binding groups and photochemical reactivities, by plankton communities in Fe‐limited subantarctic waters

2005· article· en· W1592742956 on OpenAlexafffund
María T. Maldonado, Robert F. Strzepek, Sylvia G. Sander, Philip W. Boyd

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of British Columbia
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaNational Science CouncilNational Science Foundation
KeywordsPlanktonChemistryEnvironmental chemistryPhotochemistryBioavailabilityDissociation (chemistry)PhytoplanktonIn situOceanographyBiologyOrganic chemistryNutrientGeology

Abstract

fetched live from OpenAlex

Though it is clear that plankton in oceanic regions access iron bound to strong organic ligands, the mechanism mediating the release of iron from these complexes remains unresolved. In this study, we aim to elucidate the mechanisms of organic iron acquisition by plankton in subantarctic waters. In particular, we investigated the importance of photochemistry in mediating the reductive dissociation of iron from organic complexes, using naturally occurring ligands, and model iron complexes, with different iron‐binding groups and photoreactivities. Our results demonstrate that iron within the model ligands is available for uptake and growth by indigenous plankton, but that photolability of these complexes does not determine iron bioavailability. In contrast, light significantly enhances iron acquisition from the in situ ligands, suggesting that the in situ iron ligands are photolabile, and that photochemistry in surface waters may play a significant role in iron uptake from the dissolved organic iron pool by oceanic plankton.

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 score0.004
Threshold uncertainty score0.009

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)0.0000.000

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations155
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueGlobal Biogeochemical CyclesSame topicMarine and coastal ecosystemsFrench-language works237,207