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Record W2243531792 · doi:10.82308/51862

The role of iron in the ecology and physiology of marine bacteria /

2005· dissertation· en· W2243531792 on OpenAlexfundno aff
Carol L. Adly

Bibliographic record

VenueeScholarship@McGill (McGill) · 2005
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsnot available
FundersFaculty of Graduate Studies and Research, University of AlbertaNatural Sciences and Engineering Research Council of CanadaMcGill UniversityPrinceton UniversityU.S. Department of EnergyNational Science Foundation
KeywordsBacteriaHeterotrophMicrobial metabolismBiologyCarbon cycleNutrientMarine bacteriophageCatabolismEcologyMicroorganismEnvironmental chemistryMetabolismChemistryBiochemistry

Abstract

fetched live from OpenAlex

Despite being abundant in the earth's crust, the concentration of Fe in many oceanic regions is so low that it is limiting to the growth of photosynthetic plankton. Heterotrophic bacteria play key roles in the oceanic cycling of carbon and nutrients, but it is unclear whether they can be Fe-deficient in nature, or what possible effects Fe-deficiency might have on their ecology and physiology. In chapter 1, I investigated the response of a natural bacterial community to a mesoscale Fe-enrichment experiment in the northeast subarctic Pacific. The addition of Fe to surface waters caused a rapid stimulation of bacterial growth and production, and induced the organic Fe uptake systems of bacteria. These findings suggest that bacteria responded directly to increased Fe availability, and may be Fe-deficient in situ. In chapter 2, I examined the effects of Fe-deficiency on the coupled processes of carbon catabolism and adenosine triphosphate (ATP) production in cultures of the marine bacterium Pseudoalteromonas haloplanktis. In Fe-limited cells, Fe-dependent oxidative pathways of ATP production were downregulated, leading to an intracellular energy deficit. Thus, by altering carbon metabolism and energy acquisition of heterotrophic bacteria, Fe may affect the cycling of carbon in parts of the sea.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.992

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)0.0010.000

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 head0.004
GPT teacher head0.195
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2005
Admission routes1
Has abstractyes

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