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Record W104721495 · doi:10.21236/ada453149

Human Health Safety Evaluation of Halon Replacement Candidates

2000· report· en· W104721495 on OpenAlexaboutno aff
Darol E. Dodd, G. W. Jepson, Jr Macko, Joseph Selva Kumar A

Bibliographic record

Venuenot available
Typereport
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsHuman healthEnvironmental scienceMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Environmental concern over the depletion of stratospheric ozone and global warming has led to an international treaty called The Montreal Protocol which calls for the phase out of halons by the year 2000. The services within the Department of Defense (DoD) are directed to determine and evaluate suitable halon replacement candidates that will optimize performance of mission-essential equipment and operations. Part of the evaluation process is to select halon replacement candidates that will be in compliance with environment, health, and safety considerations. In this document, a strategy for human health safety evaluation of halon replacement candidates is provided. A step-wise approach in building a chemical toxicity database, specific for halon replacement candidates, allows decisions to be made with budget and time constraints in mind. Four phases of toxicity testing are described. The confidence in predicting human health hazard increases as one proceeds from one phase of testing to the next, but the cost of each phase increases as well. Information is provided at the end of each phase that allows one to evaluate the overall benefit and cost of the tests performed before deciding to continue or stop toxicity testing of the replacement candidate. This research is part of the Department of Defense's Next-Generation Fire Suppression Technology Program (NGP), funded by the DoD Strategic Environmental Research and Development Program (SERDP). This document is part of the final reporting process for NGP Project 3B/1/89.

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 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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.045
GPT teacher head0.346
Teacher spread0.300 · 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 teacher head, not a consensus.

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
Published2000
Admission routes1
Has abstractyes

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