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Record W2020481247 · doi:10.1021/es990773r

Lead and Cadmium Interactions with Mackinawite:  Retention Mechanisms and the Role of pH

2000· article· en· W2020481247 on OpenAlexafffund
Cynthia A. Coles, S. Ramachandra Rao, Raymond N. Yong

Bibliographic record

VenueEnvironmental Science & Technology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMackinawiteChemistryFerrousMetalInorganic chemistryAdsorptionIron sulfideCadmiumEnvironmental chemistrySulfideOrganic chemistrySulfur

Abstract

fetched live from OpenAlex

The reactive iron monosulfides including mackinawite are known for their ability to scavenge trace metals. Oxidation and reduction reactions in sediments and the types of metal bonding with mackinawite determine both the stability of the metal bonds and the susceptibility of the material to oxidation. Metal retention is important because it influences the availability of toxic metals to aquatic organisms. In this study, Pb and Cd interactions with mackinawite were investigated, and two major retention mechanisms were suggested. They are, first, that Pb and Cd displace up to 29% of the Fe from mackinawite by forming (Pb,Fe)S and (Cd,Fe)S on the surface of the mackinawite and, second, that 0.91 mmol/g of Pb and 2.03 mmol/g of Cd are adsorbed on the surface of the transformed mackinawite. The mixed ferrous sulfides are more insoluble and more stable than the pure mackinawite, while surface adsorption is a relatively weak and labile retention mechanism. Both reactions contributed toward a drop in pH, although the mackinawite containing Pb and Cd was stable at this lower pH.

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 categoriesScience and technology studies, Insufficient 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 score0.234
Threshold uncertainty score0.999

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 studies0.0000.010
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.194
Teacher spread0.191 · 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

Citations88
Published2000
Admission routes2
Has abstractyes

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