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Record W6929002947 · doi:10.4224/40003280

Investigating small RPAS ground impact injury severity criteria: phase 2

2024· report· en· W6929002947 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2024
Typereport
Languageen
Field
Topic
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsPopulationHead (geology)Phase (matter)Block (permutation group theory)Human head

Abstract

fetched live from OpenAlex

The overarching goal of Phase 2 of this project was focused on investigating small remotely piloted aircraft (sRPA) to human head impact safety. Previously, a finite element (FE) model of a representative quadcopter sRPA was developed and was used to study sRPA impacts to the human head. In this phase of the project, we intended to further validate the small female human head-neck model, investigate head responses of children, and develop a new sRPA model to study head responses during the impacts with this sRPA model. This Phase 2 report is focused on 1) describing the development and validation of a new sRPA model, 2) understanding the effect of impact velocity and kinetic energy using a wood block model, and especially 3) providing comprehensive data comparing head responses for various populations under impacts with two different types of sRPA. In brief, it was found that population variances and sRPA types greatly affected head responses, and the detailed responses were investigated and documented in this report.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.091
GPT teacher head0.402
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes2
Has abstractyes

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