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Record W1983143186 · doi:10.1021/es802027f

Sorption of Strontium onto Bacteriogenic Iron Oxides

2009· article· en· W1983143186 on OpenAlexaff
S. Langley, Andrew G. Gault, Alexandre Ibrahim, Yoshio Takahashi, Rob Renaud, Danielle Fortin, Ian D. Clark, F. G. Ferris

Bibliographic record

VenueEnvironmental Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsAtomic Energy (Canada)University of TorontoUniversity of Ottawa
Fundersnot available
KeywordsSorptionStrontiumChemistryIonic strengthAqueous solutionGroundwaterIon exchangeEnvironmental chemistryNuclear chemistryAdsorptionGeologyIonOrganic chemistry

Abstract

fetched live from OpenAlex

Bacteriogenic iron oxides (BIOS) were obtained from a dilute, circumneutral groundwater seep, characterized with respect to mineralogy, and examined for their ability to sorb aqueous Sr2+. BIOS were composed of microbial sheaths encrusted in 2-line ferrihydrite. Sorption experiments indicated that Sr remained completely unbound at pH < 4.5, but sorption increased with increasing pH (maximum of 95% at pH > 7.6). EXAFS analysis of Sr-loaded BIOS failed to elucidate whether Sr sorption occurred on sites specific to the mineral or microbial fraction, but indicated that sorption likely occurred by outer-sphere complexation between BIOS and hydrated Sr2+. Sorption experiments showed that at low ionic strength (I = 0.001 M), sorption followed a Langmuir isotherm (S(max) = 3.41 mol Sr (g of Fe)(1-), K(ads) = 1.26). At higher ionic strength (I = 0.1 M), there was significant inhibition of Sr sorption (S(max) = 1.06 mol Sr (g of Fe)(1-), K(ads) = 1.23), suggesting that sorption to BIOS occurs by outer-sphere complexation. The results suggest that, under dilute circumneutral conditions, BIOS deposits should efficiently sorb dissolved Sr from groundwater flow systems where such deposits exist. This finding has particular relevance to sites impacted by radioactive 90Sr groundwater contamination.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.003
GPT teacher head0.206
Teacher spread0.203 · 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

Citations92
Published2009
Admission routes1
Has abstractyes

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