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Record W2032327600 · doi:10.1080/01490450802081820

<sup>57</sup>Fe as a Tracer of Bacterially Mediated Iron Mobilization in Lake Sediments

2008· article· en· W2032327600 on OpenAlexaff
W. Douglas Gould, S Alpay, C. W. Smith, M. Skaff, L Lortie, Marcin Pawlak

Bibliographic record

VenueGeomicrobiology Journal · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsFerrihydriteTRACEREnvironmental chemistryWater columnSedimentRedoxMicrocosmGeologyAdsorptionPrecipitationChemistryInorganic chemistryOceanography

Abstract

fetched live from OpenAlex

In simulation experiments the stable isotope, 57 Fe, was used as a novel tracer of iron transport to investigate the role of microbial activity on the distribution/redistribution of metals in lake sediments. A series of microcosm sediment columns was set up, containing a layer of 57 Fe-labelled ferrihydrite to track iron mobility temporally. Three series of columns were prepared, one set with unamended homogenized lake sediments, one set amended with 57 Fe-labelled ferrihydrite in the bottom layer of the column and one abiotic control set amended with 57 Fe-labelled ferrihydrite which was sterilized. During the experiments the iron concentrations increased in the upper sediment layers, pore water and overlying lake water and decreased in the lower amended sediment layer. The distribution of 57 Fe in the abiotic cores did not change during the experiment, implying that physical disturbance during sampling and chemical iron reduction and remobilization can be excluded as causes for the changes in iron distribution in the biotic cores. Thus, the remobilization and deposition of iron in the columns was initiated by microbial redox reactions. The implications of this work are significant for the interpretation of metal profiles in fresh water sediments as historical records of metal loadings, particularly because redox-sensitive amorphous Fe and Mn oxides and oxyhydroxides can serve as sites for metal adsorption or co-precipitation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.648
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

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)0.0080.000

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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.

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

Citations3
Published2008
Admission routes1
Has abstractyes

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