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Record W7100013609

Date

2006· article· en· W7100013609 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsnot available
Fundersnot available
KeywordsExplosive materialScanning electron microscopeAnalytical Chemistry (journal)Mass transferCarbon fibersDiffusionSoil waterMass spectrometryMorphology (biology)
DOInot available

Abstract

fetched live from OpenAlex

Understanding the transport mechanism of buried explosives in soil is crucial in order to implement an effective system for their detection. A major recurring problem is the representation of diffusion processes of these compounds on soils due their different and complex properties. The aim of this work was to describe the transport of 2, 4, 6 –Trinitrotoluene (TNT) on Ottawa sand using a mathematical model. The microscopic mass transfer of TNT on sand particles was studied using Scanning Electron Microscopy (SEM) coupled to Energy Dispersed X-ray Fluorescence Spectroscopy (EDAX). Samples of TNT on sand were analyzed varying the mass of the explosive and modifying pH conditions of sand in function of time. The images obtained from SEM showed smooth differences in the morphology and spatial distribution of the explosive on sand a few hours after sample preparation. This change in morphology and spatial distribution was found to be dependent both on the mass ratio of TNT in the sample and the pH of the sand. On the other hand, EDAX measurements showed a decrease in the nitrogen fluorescence signal intensity demonstrating that movement of TNT into the sand occurs after about eight hours; carbon measurements showed a similar behavior during this time, that is called dead time. In addition, the

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.640
Threshold uncertainty score0.998

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)0.0030.000

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 head0.005
GPT teacher head0.245
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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