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Record W2161335652 · doi:10.3122/jabfm.2011.01.100219

Neurofibromatosis Type 1: Persisting Misidentification of the "Elephant Man" Disease

2011· letter· en· W2161335652 on OpenAlexafffundabout
Claire‐Marie Legendre, Catherine Charpentier-Côté, Régen Drouin, Chantal Bouffard

Bibliographic record

VenueThe Journal of the American Board of Family Medicine · 2011
Typeletter
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversité de Sherbrooke
FundersFondation des Etoiles
KeywordsNeurofibromatosisConfusionDiseaseMedicineEthnographyNeurofibromin 1Family medicinePathologyAnthropologyPsychologyPsychoanalysisSociology

Abstract

fetched live from OpenAlex

BACKGROUND: during informal interviews in the course of an ethnographic study on intergenerational dialogue between individuals with neurofibromatosis and their parents, many members of Canadian neurofibromatosis associations have stated that they continue to be told the condition that afflicts them or their children is "elephant man's disease." Today, even though well-established clinical criteria make it possible to diagnose and differentiate the 2 diseases, the confusion between neurofibromatosis type 1 (NF1) and elephant man's disease persists in both the media's and physicians' representations. METHODS: this was an ethnographic study in medical anthropology. DISCUSSION: some reference sources and print and online news media have all contributed to the persistence of the association between NF1 and elephant man's disease. Our observations suggest that confusing NF1 with the Elephant Man's condition harms the interests of those with NF1 and thus increases the burden of the disease. CONCLUSION: changes of attitude regarding medical teaching and the media could dispel the confusion among physicians and journalists.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.288
Teacher spread0.223 · 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 designCase report
Domainnot available
GenreCommentary

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

Citations5
Published2011
Admission routes3
Has abstractyes

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