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Record W2888785183 · doi:10.1039/c8cc04751k

Fluorine-18: an untapped resource in inorganic chemistry

2018· article· en· W2888785183 on OpenAlexafffund
Cassis Varlow, Daniel Szames, Kenneth Dahl, Vadim Bernard‐Gauthier, Neil Vasdev

Bibliographic record

VenueChemical Communications · 2018
Typearticle
Languageen
FieldChemistry
TopicInorganic Fluorides and Related Compounds
Canadian institutionsUniversity of TorontoMcMaster UniversityCentre for Addiction and Mental Health
FundersCenter for Scientific ReviewNational Institute on AgingNational Institutes of HealthAzrieli FoundationCanada Research Chairs
KeywordsFluorineChemistryOrganic chemistryCombinatorial chemistryEnvironmental chemistryNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

Advances in the field of fluorine chemistry have been applied extensively to the syntheses of 18F-labelled organic compounds and radiopharmaceuticals. However, 18F has sparely been used as a tool to explore inorganic chemistry and can be viewed as a research area worthy of further development. This review highlights the application of 18F in development of inorganic fluorinating agents, mechanistic studies and imaging tools.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.007
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.005

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 head0.024
GPT teacher head0.272
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations9
Published2018
Admission routes2
Has abstractyes

Explore more

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