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Record W2911353687 · doi:10.1039/c8sc04407d

Lanthanide nanoparticles for high sensitivity multiparameter single cell analysis

2019· article· en· W2911353687 on OpenAlexafffund
Jothirmayanantham Pichaandi, Guangyao Zhao, Alexandre Bouzekri, Elsa Lu, Olga Ornatsky, Vladimir Baranov, Mark Nitz, Mitchell A. Winnik

Bibliographic record

VenueChemical Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsFluidigm (Canada)University of TorontoToronto Public Health
FundersNatural Sciences and Engineering Research Council of CanadaMitacsOntario Centres of Excellence
KeywordsLanthanideSensitivity (control systems)NanoparticleNanotechnologyMaterials scienceChemistryEngineeringOrganic chemistryElectronic engineering

Abstract

fetched live from OpenAlex

monocytes from the PBMC mixture with a 20-fold signal increase when compared to the use of only MCP-Ab conjugates. Collectively, the strong signal amplification obtained from NP reagents demonstrate the potential of these reagents to be used in conjunction with MCP-reagents to detect rare cellular markers or cell types that may otherwise be overlooked when using MCP-reagents alone.

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 score0.017
Threshold uncertainty score0.349

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 head0.009
GPT teacher head0.254
Teacher spread0.246 · 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

Citations48
Published2019
Admission routes2
Has abstractyes

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