MétaCan
Menu
Back to cohort
Record W2785692501 · doi:10.4155/bio-2017-0153

Coated Blade Spray: Shifting the Paradigm of Direct Sample Introduction to MS

2018· review· en· W2785692501 on OpenAlexaff
Germán Augusto Gómez‐Ríos, Marcos Tascón, Janusz Pawliszyn

Bibliographic record

VenueBioanalysis · 2018
Typereview
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBioanalysisComputer scienceNanotechnologySample (material)Sample preparationProcess engineeringBiochemical engineeringData scienceMaterials scienceChromatographyChemistryEngineering

Abstract

fetched live from OpenAlex

Coated blade spray (CBS) is a solid-phase microextraction-based technology that can be directly coupled to MS to enable the rapid qualitative and quantitative analysis of complex matrices. The goal of this mini review is to concisely introduce CBS's operational fundamentals and to consider how it correlates/contrasts with existing direct-to-MS technologies suitable for bioanalytical applications. In addition, we provide a fair comparison of CBS to other existing solid-phase microextraction-to-MS approaches, as well as an overview of recent CBS applications/strategies that have been developed to analyze diverse compounds present in biofluids.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.034
GPT teacher head0.320
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations60
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueBioanalysisSame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207