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Record W2802542368 · doi:10.1063/1.5035531

Recycling 100Mo for direct production of 99mTc on medical cyclotrons

2018· article· en· W2802542368 on OpenAlexaff
Joel Kumlin, Stefan Zeisler, V. Hanemaayer, Paul Schaffer

Bibliographic record

VenueAIP conference proceedings · 2018
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsTRIUMF
Fundersnot available
KeywordsHuman decontaminationDissolutionMetalPelletsMaterials scienceRadiochemistryPlating (geology)Nuclear chemistryElectrochemistryIrradiationRadioactive wasteMetallurgyChemistryWaste managementElectrode

Abstract

fetched live from OpenAlex

A scalable recycling technique for the recovery of 100Mo from previously irradiated and chemically processed targets is described. A combined process for both Cu and Ta supported targets and the respective ‘waste’ solutions has been developed. This process involves selectively dissolving Cu target backings from undissolved portions of 100Mo pellets; precipitating Cu(OH)2 at pH 9; electrochemical removal of Cu traces; precipitating (NH4)2MoO4 at pH 2.5-3; thermally decomposing (NH4)2MoO4; and H2 reduction of MoO3 to Mo metal. Radionuclidic decontamination by a factor of ~100 is observed, while overall 100Mo recovery from initial target plating to recycled Mo metal of 96% is achieved.

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)0.001
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 score0.070
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.059
GPT teacher head0.362
Teacher spread0.303 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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