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Record W6998572803

Assessing Soft-Embalmed Cadavers as a Biological Hazard

2020· dissertation· en· W6998572803 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2020
Typedissertation
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsnot available
Fundersnot available
KeywordsCadaverEmbalmingHazardBiological materials
DOInot available

Abstract

fetched live from OpenAlex

At Queen's University Department of Biomedical and Molecular Sciences, as is the case at many Canadian institutions, three primary methods are used to generate three distinct cadaver types for human anatomical education: fresh/frozen, traditional formalin hard-embalmed, and phenol-based soft-embalmed. Each of these techniques has its own merits and restrictions, with phenol-based soft-embalming combining the longevity seen in traditional embalming with the life-like quality characteristic of fresh/frozen tissue. Current environmental health and safety (EHS) restrictions place traditional formalin embalmed cadavers in Containment Level 1 (CL1) laboratories, with both fresh/frozen and phenol-based soft-embalmed cadavers in Containment Level 2 (CL2) laboratories. However, there is a gap in the current literature dictating whether or not phenol-based soft-embalmed cadavers do in fact belong in CL2 laboratories. In this hypothesis-driven report, it was hypothesised that soft-embalmed cadavers are a higher risk biosafety hazard than formalin-embalmed cadavers, thus warranted for designation to CL2 laboratories. After an in-depth analysis of the present literature surrounding the use and properties of phenol-based soft-embalmed cadavers in comparison to traditional formalin hard-embalmed cadavers, it was found that soft-embalmed cadavers do become colonized more readily by micro-organisms, aligning with our hypothesis. To definitively test the hypothesis, a proposed experiment has been suggested and outlined. In the proposed experiment, a variety of indicator species as well as CL2 designated pathogens would be tested for at regular intervals throughout the cadavers’ lifespans.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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
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
Published2020
Admission routes1
Has abstractyes

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