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Record W2083911620 · doi:10.1002/ajmg.a.33003

Fitzsimmons syndrome: Spastic paraplegia, brachydactyly and cognitive impairment

2009· article· en· W2083911620 on OpenAlexaff
Christine M. Armour, Peter Humphreys, Raoul C. M. Hennekam, Kym M. Boycott

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2009
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsDysarthriaBrachydactylySpasticMedicineSpasticityPhysical medicine and rehabilitationParaplegiaPsychologyPediatricsAudiologyCerebral palsySpinal cordPsychiatryShort stature

Abstract

fetched live from OpenAlex

Fitzsimmons syndrome is an infrequently described entity comprising slowly progressive spastic paraplegia, brachydactyly, and cone-shaped epiphyses, dysarthria, and low-normal intelligence. Five patients with this syndrome have been reported. The cause remains unknown. Here we describe a 16-year-old boy with Fitzsimmons syndrome. He was noted to toe-walk at age 18 months and spasticity progressed slowly into a spastic gait with contractures. He has mild dysarthria and hypernasal speech. Brachydactyly is notable but cannot be classified into one of the recognized types. A cone-shaped epiphysis was apparent on the only available childhood radiograph. He has moderate cognitive handicap and pervasive developmental delay. A detailed comparison of this patient with the earlier described cases is presented to further delineate the condition and increase awareness of this 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 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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.325
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 designCase report
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

Citations7
Published2009
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207