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Record W4214779743

Hip pain in an elite cyclist with Non-Hodgkin's Follicular Lymphoma: a case report.

2021· article· en· W4214779743 on OpenAlexaff
Melissa Belchos, Varsha Kumar, Carol Ann Weis

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsMedicineGynecologyFollicular lymphomaEliteChiropracticFollicular phaseLymphomaPhysical therapyGeneral surgeryPathologyInternal medicineAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: We present a case of an elite cyclist that hesitated to follow the medical advice from her practitioners, as she was determined to train and compete resulting in delayed diagnosis and management of a rare hip pathology. CASE PRESENTATION: A 51-year old elite female cyclist had a history of years of hip pain with insidious onset. The chiropractor in this case observed a lack of response to treatment, and advised the patient to get an MRI with suspicion of a labral tear. She eventually agreed to further investigations and was diagnosed with Non-Hodgkin's follicular lymphoma and a labral tear. SUMMARY: Elite athletes are not immune to serious pathology. Chiropractors should be vigilant and ensure to investigate any patients with a lack of response to conservative management. Chiropractors should be aware of the risk of athletic patients that continue to train and compete when advised not to.

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)0.003
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0060.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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