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Record W2114813580 · doi:10.1002/sia.3456

TOF‐SIMS analysis of kidney stones possibly induced by the ingestion of melamine‐ containing milk products

2010· article· en· W2114813580 on OpenAlexaff
R. N. S. Sodhi, H. Chen, S‐P. Yang, Bin Hu, Xiangtai Zeng, R‐H. Xiao

Bibliographic record

VenueSurface and Interface Analysis · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMelamineIngestionKidney stonesKidneyChemistryMicrostructureInternal medicineMedicineBiochemistryCrystallographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Ingestion of melamine contaminated food likely product kidney stones and may leads to acute kidney failure in mammals. In this study, ToF‐SIMS has been applied to imaging the micro structure of kidney stone samples, revealing information of the micro structure of different stone samples. Our data indicate that the melamine‐induce stones were formed by different mechanisms. However, information obtained using other techniques is also required to correlate the detailed differences in the microstructure of the stone samples with the formation mechanism. Copyright © 2010 John Wiley & Sons, Ltd.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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