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Record W7145652795

低濃縮ウラン(LEU)からの99Mo製造プロセスに関する調査

2011· report· ja· W7145652795 on OpenAlexaboutno aff
Masataka Tanimoto, D. Amaya, Masashi Aoyama, Akihiro Kimura, Hironobu Izumo, Kunihiko Tsuchiya

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2011
Typereport
Languageja
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)CountermeasureShutdownProcess (computing)Atomic energyNuclear power
DOInot available

Abstract

fetched live from OpenAlex

Recently, worldwide demand of $^{99}$Mo became rises. However the availability and supply of $^{99}$Mo for the manufacturing of generators has been a matter of concern. Concern arose from several factors including, amongst others, the shutdown of some nuclear reactors at Canada (NRU, etc.), uncertainty of reliable operating condition for radioisotope production and difficulties in the availability of highly enriched $^{235}$U (HEU) target material used in the majority of the production facilities. As countermeasure for this issue, the HEU is not used but $^{99}$Mo production from low enriched $^{235}$U (LEU) is performed. This production process was developed in Argentina by the Argentine Atomic Energy Commission (CNEA). In the last ten years, INVAP has been working in the supply of $^{99}$Mo production facilities using LEU. This report provides descriptions for the detail technical aspects related to a $^{99}$Mo production system using irradiated LEU targets.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.013
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.038

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 head0.070
GPT teacher head0.301
Teacher spread0.231 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueInstitutional Repositories DataBase (IRDB)French-language works237,207