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Record W3104252006 · doi:10.22215/etd/2020-14173

A Study of the Impact Response of Discrete Regions of the Human Cadaver Brain

2020· dissertation· en· W3104252006 on OpenAlexafffund
Scott Dutrisac

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsCarleton UniversityRoyal Ottawa Mental Health CentreUniversity of Ottawa
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsDisplacement (psychology)Cadaveric spasmCorpus callosumHead (geology)Brain traumaHuman headComputer scienceFinite element methodEngineeringStructural engineeringTraumatic brain injuryNeuroscienceGeologyMedicinePsychologyAnatomy

Abstract

fetched live from OpenAlex

The risk of trauma to the brain due to head impacts is high, despite widespread use of protective equipment and injury mitigation efforts. Mitigation techniques are developed through simulations that utilize complex finite element models of the brain and head. Validation of such models is limited, as existing empirical data is sparse. Due to technical constraints, empirical studies have only revealed broad brain tissue deformation. The objective of this study was to develop a comprehensive methodology for measuring the displacement of discrete brain structures during impact. An advanced X-ray system was used to capture brain motion for two cadaveric specimens at 7,500 fps. Displacement of brain structures was determined for 7 impacts on each specimen. Motion trends were region dependent, with some regions exhibiting multi-modal displacement. Displacement of discrete structures including the corpus callosum was measured. These methods will help clarify the response of the brain to impact.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

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

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 head0.036
GPT teacher head0.365
Teacher spread0.330 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2020
Admission routes2
Has abstractyes

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