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Record W3205863181 · doi:10.1128/jcm.01398-21

Multicenter Evaluation of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy-Based Method for Rapid Identification of Clinically Relevant Yeasts

2021· article· en· W3205863181 on OpenAlexafffund
Lisa M. T. Lam, Ashraf A. Ismail, Simon Lévesque, Simon F. Dufresne, Mathew P. Cheng, Émilie Vallières, Me‐Linh Luong, Jacqueline Sedman, Philippe J. Dufresne

Bibliographic record

VenueJournal of Clinical Microbiology · 2021
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsHôpital Maisonneuve-RosemontSte. Anne's HospitalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Hospitalier de l’Université de MontréalMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanMcGill University Health CentreCentre Hospitalier Universitaire de SherbrookeCentre Hospitalier Universitaire Sainte-JustineUniversité de SherbrookeUniversité Sainte-Anne
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsAttenuated total reflectionFourier transform infrared spectroscopyInfraredFourier transformMulticenter studyFourier transform spectroscopyInfrared spectroscopySpectroscopyMedicineChemistryPathologyOpticsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

= 24) isolates were obtained for evaluation and resulted in 100% correct identification. Overall, the data obtained in our multicenter evaluation study using multiple spectrometers and system operators indicate that ATR-FTIR spectroscopy is a reliable, cost-effective yeast identification technique that provides accurate and timely (∼3 min/sample) species identification promptly after the initial culture.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.298
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.045
GPT teacher head0.393
Teacher spread0.348 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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