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Record W4392353446 · doi:10.3389/fcomm.2024.1267065

Seizing the moment: communicating ethics, decisions, and neurotechnological approaches to pediatric drug-resistant epilepsy

2024· article· en· W4392353446 on OpenAlexaff
Judy Illes, Patrick J. McDonald, George M. Ibrahim, Mary Connolly, Robert P. Naftel, Marianne Bacani, Anna Nuechterlein, Samantha P. Go, Johann Roduit

Bibliographic record

VenueFrontiers in Communication · 2024
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsHospital for Sick ChildrenBC Children's HospitalUniversity of ManitobaNeuroDevNetUniversity of British Columbia
FundersNational Institutes of Health
KeywordsEpilepsyDrugMedicinePsychiatryPsychology

Abstract

fetched live from OpenAlex

It is a fundamental duty of neuroscientists to discuss the results of research and related ethical implications. Engagement with neuroscience is especially critical for families with children affected by disorders such as drug resistant epilepsy (DRE) as they navigate complex decisions about innovations in treatment that increasingly include invasive neurotechnologies. Through an evidence-based, iterative, and value-guided approach, we created the short-form documentary film, Seizing Hope: High Tech Journeys in Pediatric Epilepsy , to delve into the relationship between experts with first-hand, lived experience – youth with DRE and caregivers – and physician experts as they weigh medical and ethical trade-offs on this landscape. We describe the co-creation and evolution of this film, screenings, and feedback. Survey responses from 385 viewers highlight new developments in technologies for the treatment of DRE, how families navigate choices for treatment with brain technology, and a sense of hope for the future for children with epilepsy as key attributes of this science communication piece.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.417
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.158
GPT teacher head0.335
Teacher spread0.176 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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