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Record W3188526236 · doi:10.1039/d1cc03030b

N-Heterocyclic carbenes meet toll-like receptors

2021· article· en· W3188526236 on OpenAlex
Ishwar Singh, Dianne Lee, Shuaishuai Huang, Hridaynath Bhattacharjee, Wei Xu, Jennifer F. McLeod, Cathleen M. Crudden, Zhe She

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Communications · 2021
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTollReceptorChemistryCombinatorial chemistryStereochemistryBiologyBiochemistryImmunology

Abstract

fetched live from OpenAlex

Combining the stability of the N-heterocyclic carbenes (NHCs) and broad-spectrum recognition of toll-like receptor (TLR) proteins, we report new electrochemical biosensors for bacteria detection. Instead of traditional thiol-gold chemistry, newly synthesized NHCs are employed as the linker molecules to immobilize TLR bio-recognition elements on gold electrodes. Our proof-of-concept methodology includes testing the fidelity of TLR-based electrochemical sensors with NHC linkers. The performance of the biosensors is demonstrated using whole-cell bacterial cultures.

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.

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 categoriesInsufficient 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 score0.307
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.291
Teacher spread0.255 · 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