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Record W2936840653 · doi:10.1039/c9ra01396b

Sensitive Raman detection of human recombinant interleukin-6 mediated by DCDR/GERS hybrid platforms

2019· article· en· W2936840653 on OpenAlexfundno aff
Emmanuel de la O-Cuevas, Isidro Badillo‐Ramírez, Selene R. Islas, C. Araujo-Andrade, José M. Sániger

Bibliographic record

VenueRSC Advances · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsnot available
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoConsejo Nacional de Ciencia y TecnologíaCanadian Institute for Theoretical Astrophysics
KeywordsRecombinant DNARaman spectroscopyInterleukin 1βComputational biologyChemistryInterleukinNanotechnologyMaterials scienceBiologyImmunologyBiochemistryPhysicsCytokineGeneOptics

Abstract

fetched live from OpenAlex

. It is important to note that this result implies the absolute mass detection of 1 fg of IL-6. In summary, the Raman spectroscopy DCDR/GERS analytical platform proposed here allows the reliable identification of, as well as the very sensitive detection of, IL-6 and promises to improve the performance of clinical evaluations of this biomarker that are currently in use. In this study, the Raman spectra of IL-6 in powder and solution, together with the corresponding band assignment, are presented for the first time in the literature.

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 score0.038
Threshold uncertainty score0.404

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 head0.005
GPT teacher head0.291
Teacher spread0.285 · 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

Citations27
Published2019
Admission routes1
Has abstractyes

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