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Record W4224951780 · doi:10.3389/fcell.2022.885440

Fluorescent Indicators For Biological Imaging of Monatomic Ions

2022· review· en· W4224951780 on OpenAlexafffund
Sheng-Yi Wu, Yi Shen, Irene Shkolnikov, Robert E. Campbell

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2022
Typereview
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsUniversity of VictoriaUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMonatomic ionBiological fluidsNanotechnologyBiochemical engineeringIonComputer scienceChemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Monatomic ions play critical biological roles including maintaining the cellular osmotic pressure, transmitting signals, and catalyzing redox reactions as cofactors in enzymes. The ability to visualize monatomic ion concentration, and dynamic changes in the concentration, is essential to understanding their many biological functions. A growing number of genetically encodable and synthetic indicators enable the visualization and detection of monatomic ions in biological systems. With this review, we aim to provide a survey of the current landscape of reported indicators. We hope this review will be a useful guide to researchers who are interested in using indicators for biological applications and to tool developers seeking opportunities to create new and improved indicators.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.261
Teacher spread0.239 · 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 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

Citations24
Published2022
Admission routes2
Has abstractyes

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