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Record W2052187078 · doi:10.2136/sssaj2000.643885x

Perturbation of Taranakite Formation by Ferrous and Ferric Iron under Acidic Conditions

2000· article· en· W2052187078 on OpenAlexafffund
Jianmin Zhou, C. Liu, P. M. Huang

Bibliographic record

VenueSoil Science Society of America Journal · 2000
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFerrousChemistryCrystallizationNucleationFerricPhosphateMolar ratioSoil waterInorganic chemistryMolarIonFERRIC IRONNuclear chemistryCatalysisGeology

Abstract

fetched live from OpenAlex

Taranakite is an important reaction product of monoammonium phosphate fertilizer with soils. Its formation affects the transformation of nutrients in soils. The effect of different molar ratios of Fe(II)/Al and Fe(III)/Al on the formation of taranakite at pH 4.0 was investigated in this study. The results show that Fe(II) ion significantly perturbed the formation of taranakite at the Fe/Al molar ratio of 1.2 When the Fe/Al molar ratio was increased to 2.5, the formation of taranakite was completely inhibited by Fe(II), whereas, under the same condition, some crystalline taranakite was still observed in the Fe(III) system. Although Fe(III) had less effect on the crystallization of taranakite than Fe(II) at lower Fe/Al molar ratios, it also completely inhibited the formation of taranakite at the molar ratio of Fe(III)/Al ≥ 5. The solid products formed in the Fe(III) or Fe(II) system contained a substantial amount of Fe(III) and a much higher proportion of phosphate than that was required for the formation of NH 4 –taranakite. As indicated by the solution phase analysis at the end of the experiment, more Fe ions were present in the solution in the Fe(II) system, compared with the Fe(III) system, to perturb the nucleation and crystallization of taranakite. Since iron is a very common element in soil, taranakite formation may be perturbed in soils with high Fe content, especially under reduced and acidic conditions.

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 categoriesnone
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 score0.209
Threshold uncertainty score0.524

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 studies0.0000.001
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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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

Citations8
Published2000
Admission routes2
Has abstractyes

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