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Record W7146543678

地質環境の長期安定性に関する研究 年度報告書(令和元年度)

2020· report· ja· W7146543678 on OpenAlexfundno aff
Tsuneari Ishimaru, Nobuhisa Ogata, Yoko Kokubu, Koji Shimada, Takahiro Hanamuro, Akiomi Shimada, Masakazu Niwa, Koichi Asamori, Takahiro Watanabe, Shigeru Sueoka, Tetsuya Komatsu, Tatsunori Yokoyama, Natsuko Fujita, Mayuko Shimizu, Yasuhiro Ogita, Saya Kagami, Akira Goto

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2020
Typereport
Languageja
Field
Topic
Canadian institutionsnot available
FundersJapan Atomic Energy AgencyNuclear Waste Management Organization
KeywordsDevelopment planPlan (archaeology)Scientific developmentEstimationScientific literature
DOInot available

Abstract

fetched live from OpenAlex

This annual report documents the progress of research and development (R\&D) in the 5th fiscal year during the JAEA 3rd Mid- and Long-term Plan (fiscal years 2015-2021) to provide the scientific base for assessing geosphere stability for long-term isolation of the high-level radioactive waste. The planned framework is structured into the following categories: (1) Development and systematization of investigation techniques, (2) Development of models for long-term estimation and effective assessment, (3) Development of dating techniques. The current status of R\&D activities with previous scientific and technological progress is summarized.

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)0.016
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.009
Science and technology studies0.0020.001
Scholarly communication0.0150.007
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.053

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 head0.052
GPT teacher head0.305
Teacher spread0.253 · 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
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
Published2020
Admission routes1
Has abstractyes

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