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Record W2895220281 · doi:10.1039/c8sc03692f

Hybrid CuCoO–GO enables ultrasensitive detection of antibiotics with enhanced laser desorption/ionization at nano-interfaces

2018· article· en· W2895220281 on OpenAlexaff
Enhui Wu, Kun Feng, Rui Shi, Rui Lv, Fuzhong Ouyang, Shawn S.‐C. Li, Jun Zhong, Jian Liu

Bibliographic record

VenueChemical Science · 2018
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
FundersNational Natural Science Foundation of ChinaNational Synchrotron Radiation LaboratoryCollaborative Innovation Center of Suzhou Nano Science and TechnologyHigher Education Discipline Innovation ProjectPriority Academic Program Development of Jiangsu Higher Education InstitutionsRecruitment Program of Global Experts
KeywordsIonizationNano-DesorptionLaserNanotechnologyMatrix-assisted laser desorption/ionizationMatrix (chemical analysis)AntibioticsMaterials scienceChemistryChromatographyOpticsPhysicsAdsorptionIonOrganic chemistry

Abstract

fetched live from OpenAlex

)-labeled analyte as the internal standard. Our experiments have achieved lower limits of detection (LOD) by several hundred fold for the detection of a panel of representative antibiotics, in comparison with the literature reports. Both intrabacterial and extrabacterial residual antibiotics can be sensitively detected with our method. We have further investigated the molecular mechanism of the enhanced desorption/ionization efficiency by the CuCoO-GO matrix with synchrotron radiation techniques for the first time. This work provides a sensitive matrix enabling MALDI-TOF MS to be applied in small molecular analysis, but also presents a distinct perspective on the mechanism behind the material functions.

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 score0.019
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.232
Teacher spread0.225 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

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