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Record W2270042541

질소가스를 이용한 청정 소화시스템의 개발

2006· article· ko· W2270042541 on OpenAlexaboutno aff
박재만, 이택구, 박동하, 이성모, 김영경

Bibliographic record

Venue유체기계 연구개발 발표회 논문집 · 2006
Typearticle
Languageko
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPipingEnvironmental scienceWaste managementInert gasNitrogen gasEngineeringNitrogenEnvironmental engineeringChemistryChemical engineering
DOInot available

Abstract

fetched live from OpenAlex

Under the Montreal Protocol the production of halon fire extinguishing agent has been phased out throughout the developed world. Recently Shinwha Electronics began developing, testing and producing total-flood fire suppression systems containing nitrogen gas as the agent. These systems are designed to replace Halon 1301 total-flood systems in a variety of applications. The nitrogen gas systems consist of an agent cylinder, discharge manifold, activation valves, distribution piping, nozzles, pipe hangers and detection/control devices. There are no degradation byproducts resulting from the manufacture, processing, use, or disposal of nitrogen gas. Nitrogen gas is the cheapest agent available, effective as the other inert gases, non-toxic and suitable for occupied spaces.

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)0.006
metaresearch head score (Gemma)0.010
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.398
Threshold uncertainty score0.859

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0050.002
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.3980.249

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 head0.004
GPT teacher head0.173
Teacher spread0.168 · 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 designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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