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Record W2168098609

심해무인잠수정 운용사례 분석을 통한 해미래의 운용 전략 수립

2012· article· ko· W2168098609 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

Venue한국해양환경·에너지학회 학술대회논문집 · 2012
Typearticle
Languageko
FieldEngineering
TopicAdvanced Algorithms and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsRemotely operated underwater vehicleRemotely operated vehicleMarine engineeringMetreSeabedGeologyRemote sensingEnvironmental scienceEngineeringOceanographyComputer scienceArtificial intelligenceMobile robotRobot
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we analyze the operating methods of the ROVs( Remotely Operated Vehicle ) and conduct a study on how to apply these methods to our self-developed 6,000 meter class ROV HEMIRE. The used data in this paper were collected from the expedition of JASON ROV of USA to retrieve a junction box installed on seabed 5,000 meter between Hawaii and California for maintenance during June 20th ~ July 11th 2004 and ROPOS ROV of Canada to explore the hydrothermal deposit located Tonga, southpacific, on January 12th ~ February 1st 2012. Through the analysis, we could arrange the applicable skills with HEMIRE system and strategy to carry out as an independent mode by itself.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.006

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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