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Record W4298619152 · doi:10.1186/s41181-022-00177-w

Highlight selection of radiochemistry and radiopharmacy developments by editorial board

2022· review· en· W4298619152 on OpenAlexaff
Jun Toyohara, Mohammed Al‐Qahtani, Ya-Yao Huang, Emiliano Cazzola, Sergio Todde, Shozo Furumoto, Renata Mikołajczak, Clemens Decristoforo, Nic Gillings, Min Yang, Raymond M. Reilly, Adriano Duatti, Antonia G. Denkova, Ralf Schirrmacher, Giuseppe Carlucci, Yann Seimbille, Zhaofei Liu, Beverley L. Ellis, Bart Cornelissen, Klaus Kopka, Emerson Soares Bernardes

Bibliographic record

VenueEJNMMI Radiopharmacy and Chemistry · 2022
Typereview
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of AlbertaUniversity of Toronto
FundersMedical Research CouncilCancer Research UK
KeywordsEditorial boardScope (computer science)Audience measurementMedical physicsRadiochemistryComputer scienceLibrary scienceChemistryMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The Editorial Board of EJNMMI Radiopharmacy and Chemistry releases a biannual highlight commentary to update the readership on trends in the field of radiopharmaceutical development. MAIN BODY: This commentary of highlights has resulted in 21 different topics selected by each coauthoring Editorial Board member addressing a variety of aspects ranging from novel radiochemistry to first in man application of novel radiopharmaceuticals. CONCLUSION: Trends in radiochemistry and radiopharmacy are highlighted demonstrating the progress in the research field in various topics including new PET-labelling methods, FAPI-tracers and imaging, and radionuclide therapy being the scope of EJNMMI Radiopharmacy and Chemistry.

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)0.006
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0350.021

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 head0.028
GPT teacher head0.347
Teacher spread0.319 · 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
GenreEditorial

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

Citations4
Published2022
Admission routes1
Has abstractyes

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