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Record W4200593554 · doi:10.9798/kosham.2021.21.6.53

Development of Standard Operating Procedure (SOP) Training Model Using Disaster Safety Communication Network Based on Public Safety Long Term Evolution (PS-LTE)

2021· article· en· W4200593554 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKorean Society of Hazard Mitigation · 2021
Typearticle
Languageen
FieldComputer Science
TopicTechnology and Data Analysis
Canadian institutionsCapcom Vancouver (Canada)
FundersDivision of Civil, Mechanical and Manufacturing InnovationKorea Forest Service
KeywordsCapability Maturity Model IntegrationStandard operating procedureProcess (computing)Training (meteorology)BusinessOperations managementEngineeringProcess managementComputer science

Abstract

fetched live from OpenAlex

This study provides information for developing the domestic standard operating procedure (SOP) to CMMI level 3 or higher by presenting the SOP education and training model development process that systematically utilize the PS-LTE-based disaster safety communication network. The survey was conducted with 113 domestic SOP experts. Results revealed that four strategies can minimize the damage to people's lives and property in a national disaster and develop the domestic SOP level to CMMI level 3 or higher-establishment of governance for the SOPs for disaster safety communication networks; training on SOP once a year; establishment of SOP according to the guidelines; and improvement in the technical field. In the future, if SOP develops to CMMI level 3 or higher, it will contribute to the protection of public safety and property from disasters.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.383
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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