MétaCan
Menu
Back to cohort
Record W2039283405 · doi:10.5762/kais.2009.10.7.1735

A Study on Trend of Technology Development for Unmanned Combat Ground Vehicle

2009· article· en· W2039283405 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of the Korea Academia-Industrial cooperation Society · 2009
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)Key (lock)Technology developmentEmerging technologiesAeronauticsEngineeringComputer scienceComputer securityManufacturing engineering

Abstract

fetched live from OpenAlex

지상무인 전투체계에서 요구되는 원천, 핵심기술은 해외 선진 국가들과의 치열한 경쟁이 예상된다. 따라서 주요 국가의 무인체계 기술개발현황을 분석하였으며, 분석 대상은 1998년부터 2008년까지 미국, 일본, 유럽, 캐나다, 이스라엘 등에 출원된 현황을 기준하였다. 주요 선진국의 특허맵과 전문가 의견을 수렴하여 국가별 기술 수준, 역점분야와 공백기술, 시장력 등을 분석하였으며, 앞으로 발전 가능성이 예상되는 기술과 우리나라가 중점 개발하여야할 분야 등을 제시하였다. The keen global competition is expected among foreign advanced nations for source, key technologies required by unmanned combat ground vehicle. Therefore, the trend of technologies for unmanned ground combat vehicle was analyzed in this research. It was based on the submitted patents from 1988 to 2008 in Korea, U.S.A, Japan, Europe, Canada and Israel. This analysis was focused on finding the technical level, the challenge area and breakthrough technologies and the growth of technologies of each nations considering opinions of experts. This report suggested the field of key technology development

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.

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)0.001
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.001
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 head0.046
GPT teacher head0.290
Teacher spread0.244 · 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