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Record W4400237906 · doi:10.1097/wco.0000000000001288

Editorial introductions

2024· article· en· W4400237906 on OpenAlexaboutno aff

Bibliographic record

VenueCurrent Opinion in Neurology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary Sociological Theory and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Current Opinion in Neurology was launched in 1988. It is one of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of neurology is divided into 14 sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Journal's Section Editors for this issue. SECTION EDITORS Martin J. McKeownMartin J. McKeownDr McKeown is the John Nichol Chair in Parkinson's Research, Professor and Head of the Division of Neurology in the Department of Medicine, and adjunct professor in the Department of Electrical and Computer Engineering at the University of British Columbia, Vancouver, Canada. He did his Engineering Physics, Medicine and Neurology training at McMaster, University of Toronto, and University of Western Ontario, Canada, respectively. He did a three-year research fellowship at the Computational Neurobiology Laboratory at the Salk Institute for Biological Studies in San Diego, USA, before being hired as an Assistant Professor of Medicine and Biomedical Engineering at Duke University, USA. He was recruited to UBC in 2003. He is currently the Medical Advisor to the Parkinson's Society of BC and Chair of the Research and Clinical Advisory Committee of Parkinson Canada. His research interests include using brain imaging to guide non-invasive neuromodulation development and privacy-compliant video monitoring technologies for Parkinson's disease. Per SvenningssonPer SvenningssonPer Svenningsson is Professor in Neurology at the Karolinska Institutet and King's College London. He received his MD and PhD from Karolinska Institutet, Sweden. He then did his postdoctoral training in the laboratory of the Nobel laureate Paul Greengard at the Rockefeller University, USA. His studies concerned GPCR neuropharmacology and signal transduction and included the discovery of p11 as an important modulator of serotonin neurotransmission. He performed his residency in Neurology at Karolinska University Hospital and became Professor in 2012 and senior consultant in 2016. Since 2018, he is also parttime Professor of Neurodegeneration at King's College London, UK. His research interests include GPCR pharmacology, Parkinson's disease both its motor and non-motor aspects and atypical parkinsonism. Studies are conducted both in preclinical models and in specimens from patients. The goal is to identify novel targets for improved diagnostics and pharmacological therapies. Biochemical, histological, pharmacological, molecular biological and behavioral techniques are used. In the clinics, he is conducting clinical trials with therapies aiming to slow down progression of Parkinson's disease or to treat debilitating symptoms of the disease. He has published more than 300 articles. He is member of the Nobel Assembly annually awarding the Nobel Prize in Physiology or Medicine, the Swedish Royal Academy of Sciences, ACNP, Academica Europae and the International Executive Committee of MDS. He delivered the Eurolife Distinguished Medal Lecture in Barcelona and the Allan D Bass lecture in Nashville. He has been awarded the Arvid Carlsson Prize.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.412
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.431
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreEditorial

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 routes1
Has abstractyes

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