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Record W3196289415

HIDDEN NANO CHEMISTRY IN BENDICT GLUCOSE TEST

2012· article· en· W3196289415 on OpenAlexvenueno aff
Nargish Parvin, Tapas Kumar Mandal

Bibliographic record

VenueCanadian Journal of Applied Sciences · 2012
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
Fundersnot available
KeywordsBlood sugarSugarTRACE (psycholinguistics)Qualitative analysisChemistryDiabetes mellitusChromatographyFood scienceMedicineEndocrinologyQualitative researchPhilosophySociology
DOInot available

Abstract

fetched live from OpenAlex

From centuries, different manufacturers are using different technology for blood glucose monitoring. Since 1908, Benedict's test is utilized for only qualitative analysis of the urine/blood sample of patients suspected for diabetics mellitus. Based on this fact, we have now experimentally proved that presence of nanosized cuprous oxide equivalent to the reduced sugar present in any biological fluid can be utilized for both the qualitative and quantitative analysis of even trace amount of sugar in different species using fluorescence spectroscopy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.185
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Applied SciencesSame topicElectrochemical sensors and biosensorsFrench-language works237,207