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Record W2916276487 · doi:10.18910/55432

山中永之佑名誉教授に聞く : 大阪大学の思い出(2)

2012· article· ja· W2916276487 on OpenAlexaboutno aff
真城 菅, 敏充 中尾, 武司 阿部

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2012
Typearticle
Languageja
FieldEngineering
TopicStonefly species taxonomy and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This is a record of the talk of Professor Emeritus Einosuke Yamanaka related to the history of the Faculty of Law at the Osaka University. When Professor Yamanaka was Dean of the faculty in 1983-85, he soon cleared the suspicion that the faculty was related to a corruption case of the university. Thereafter he increased the number of students by the institutional changes, created the chair of Comparative Legal Cultures, and concluded the inter-faculty exchange agreement with the University of British Columbia in Canada. Professor Yamanaka continued to conduct research about legal history, particularly on Japanese bureaucracy, local government and family system, often with many excellent scholars not only in Osaka University but also in the other universities. He published many academic books and articles, and also compiled lots of local histories organized by the local governments. Professor Yamanaka worked as a member of the Science Council of Japan during the period from 1988-97, and made efforts to establish the archives of Osaka Prefecture. He also promoted the disclosure of the governmental information, and often gave legal advice at a court.

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)0.001
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.004
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.004

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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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
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

Citations0
Published2012
Admission routes1
Has abstractyes

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