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Record W2618661190 · doi:10.1021/acs.analchem.7b01382

Deposition of a Sorbent into a Recession on a Solid Support To Provide a New, Mechanically Robust Solid-Phase Microextraction Device

2017· article· en· W2618661190 on OpenAlexafffund
Justen Poole, Jonathan J. Grandy, Miao Yu, Ezel Boyacı, Germán Augusto Gómez‐Ríos, Nathaly Reyes‐Garcés, Barbara Bojko, Harmen Vander Heide, Janusz Pawliszyn

Bibliographic record

VenueAnalytical Chemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
FundersQuébec Consortium for Drug DiscoveryMerck CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaFondation Brain CanadaPfizer CanadaOntario Brain Institute
KeywordsSolid-phase microextractionChemistrySorbentDeposition (geology)Solid surfaceSolid-phase synthesisPhase (matter)Solid solutionChromatographyChemical engineeringAdsorptionOrganic chemistryGas chromatography–mass spectrometryChemical physicsMass spectrometry

Abstract

fetched live from OpenAlex

To date, solid-phase microextraction (SPME) fibers used for in vivo bioanalysis can be too fragile and flexible, which limits suitability for direct tissue sampling. As a result, these devices often require a sheathing needle to prepuncture robust sample matrixes and protect the extraction phase from mechanical damage. To address this limitation, a new SPME device is herein presented which incorporates an extraction phase recessed into the body of a solid needle. This device requires no additional support or shielding during puncture events through protective tissue. The presented device was thoroughly tested, being fired at 90 m·s –1 through fish scales, forced through vial septa, and employed in a targeted study of polyunsaturated fatty acids in salmon where the protective outer skin was repetitively punctured during sampling. Finally, the recessed SPME device was applied to an on-site application for the tissue analysis of wild muskellunge. With this advancement, rapid, minimally invasive, and easily executed in vivo SPME is now possible opening the door to near endless sampling opportunities.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.398
Teacher spread0.350 · 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 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

Citations46
Published2017
Admission routes2
Has abstractyes

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