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Record W2357404242 · doi:10.1590/0004-282x20160040

What’s in a name? Problems, facts and controversies regarding neurological eponyms

2016· review· en· W2357404242 on OpenAlexaff
Hélio A.G. Teive, Plínio M.G. de Lima, Francisco Manoel Branco Germiniani, Renato P. Munhoz

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2016
Typereview
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsEponymMedicineNeurologySubject (documents)PediatricsDiseasePsychiatryPathologyComputer scienceLibrary science

Abstract

fetched live from OpenAlex

The use of eponyms in neurology remains controversial, and important questions have been raised about their appropriateness. Different approaches have been taken, with some eponyms being excluded, others replaced, and new ones being created. An example is Hallervorden-Spatz syndrome, which has been replaced by neurodegeneration with brain iron accuulatium (NBIA). Amiothoplic lateral sclerosys (ALS), for which the eponym is Charcot's disease, has been replaced in the USA by Lou Gehrig's disease. Guillain-Barré syndrome (GBS) is an eponym that is still the subject of controversy, and various different names are associated with it. Finally,restless legs syndrome (RLS), which was for years known as Ekbom's syndrome, has been rechristened as RLS/Willis-Ekbom syndrome.

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)0.005
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.068
GPT teacher head0.327
Teacher spread0.259 · 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
GenreReview

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

Citations4
Published2016
Admission routes1
Has abstractyes

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