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Record W4382134477 · doi:10.1016/s1452-3981(23)13023-9

Recent Advancement in Various Electrochemical and Immunosensing Strategies for Detection of Chloramphenicol

2013· article· en· W4382134477 on OpenAlexaboutno aff
Shabi Abbas Zaidi

Bibliographic record

VenueInternational Journal of Electrochemical Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsnot available
FundersKwangwoon University
KeywordsMiniaturizationChloramphenicolBroad spectrumNanotechnologyComputer scienceBiochemical engineeringMaterials scienceAntibioticsChemistryEngineeringCombinatorial chemistry

Abstract

fetched live from OpenAlex

The application of Chloramphenicol (CAP), a broad spectrum antibiotic, has been restricted in poultry, aquatic and other food producing animals in EU, Canada and US completely due to its numerous toxic, adverse and fatal side effects in human and veterinary. Hence, there is a constant requirement for accurate, simpler, faster and improved analytical method for its detection. Several methods have been developed and appeared in literature for the detection of CAP. Among all the techniques, the immonosening and electrochemical methods have been considered the foremost methods because of their unique features. The immunosensor show great sensitivity and selectivity, on the other hand low cost, easy operation, fast response time and excellent potential for miniaturization and construction for portable equipment applications make electrochemical sensors as preferred choice. Thus, this mini review brings the various immunosensing and electrochemical strategies applied for the preparation of CAP sensor in last twelve years (from 2000-2013) on one platform.

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 score0.049
Threshold uncertainty score0.292

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)0.0000.000

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 head0.006
GPT teacher head0.285
Teacher spread0.279 · 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

Citations36
Published2013
Admission routes1
Has abstractyes

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