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Record W170226984 · doi:10.2320/materia.45.48

[no title]

2006· article· ja· W170226984 on OpenAlexaff
Shigeharu Ukai, Takeji Kaito, Satoshi Ohtsuka, Masayuki Fujiwara, Toshimi Kobayashi

Bibliographic record

VenueMateria Japan · 2006
Typearticle
Languageja
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsMaterials science

Abstract

fetched live from OpenAlex

HT9等のフェライト系耐熱鋼は格段に優れた中性子照射損傷抵抗性を有していることから、原子力の高速炉分野において燃焼度200GWd/tの高燃焼度燃料の被覆管材料としてこれまで使用されてきた。しかし、フェライト系はオーステナイト系の耐熱鋼に比べて高温強度が劣ることから、その使用温度は873K以下に制限されている。この課題を克服して高速炉の高効率運転を実現すべく、照射損傷抵抗性に優れたフェライト鋼中にY2O3粒子を分散してその高温強度を向上させた酸化物分散強化型(Oxide dispersion Strengthened)フェライト鋼の開発がこれまで行われてきた。しかし金属粉末とY2O3粉末のメカニカルアロイング(MA)処理粉末を固化成形したODSフェライト鋼は硬くて脆い難加工性材料であることから、固化成形体からの冷間圧延による被覆管への製管はこれまで不可能であった。これに対して著者らは、その組織制御技術を独自に開発することにより、世界で初めて冷間圧延による被覆管製造を可能にするとともに、酸化物粒子のナノ制御技術を開発して、フェライト系耐熱鋼管としては世界最高の高温強度を有する9Cr-ODSフェライト/マルテンサイト鋼被覆管を実用化した。

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.009

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 head0.010
GPT teacher head0.219
Teacher spread0.208 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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