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Record W2588603895 · doi:10.1134/s1063779617010075

Production of medical 99m Tc isotope via photonuclear reaction

2017· article· en· W2588603895 on OpenAlexaboutno aff
Mamoru Fujiwara, K. Nakai, N. Takahashi, Takehito Hayakawa, T. Shizuma, S. Miyamoto, Gong-Tao Fan, Akinori Takemoto, Masashi Yamaguchi, Makoto Nishimura

Bibliographic record

VenuePhysics of Particles and Nuclei · 2017
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsIsotopeNuclear physicsProduction (economics)Particle physics

Abstract

fetched live from OpenAlex

99m Tc with a 6 hour half-life is one of the most important medical isotopes used for the Single-Photon Emission Computed Tomography (SPECT) inspection in hospitals of US, Canada, Europe and Japan. 99m Tc isotopes are extracted by the milking method from parent 99Mo isotopes with a 66 hour half-life. The supply of 99Mo isotopes now encounters a serious crisis. Hospitals may not suitably receive 99Mo medical isotopes in near future, due to difficulties in production by research nuclear reactors. Many countries are now looking for alternative ways to generate 99Mo isotopes other than those with research reactors. We discuss a sustained availability of 99m Tc isotopes via the nat Mo(γ, n) photonuclear reaction, and discuss to solve technical problems for extracting pure 99m Tc isotopes from other output materials of photonuclear reactions.

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 score0.032
Threshold uncertainty score0.184

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 head0.046
GPT teacher head0.352
Teacher spread0.306 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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