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Record W63631855

Varied clinical presentation of os odontoideum: a case report.

2014· article· en· W63631855 on OpenAlexaff
Karen Chrobak, Ryan Larson, Paula Stern

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsHuntington Society of CanadaCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticMedicineSpinal manipulationNeck painPresentation (obstetrics)RadiographyMedical diagnosisManual therapyPhysical examinationMagnetic resonance imagingCervical vertebraeRadiologyAtlantoaxial instabilityPhysical therapyCervical spineSurgeryAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To present a case of an os odontoideum and to provide insight into the varied clinical presentations. CLINICAL FEATURES: A 54 year old man presented with chronic neck pain without headache. A clinical examination was performed and the chiropractor viewed his AP and lateral radiographs. Previous flexion/ extension radiographs and MRI imaging from 2009 were requested for review. The patient was diagnosed with grade II mechanical neck pain. Treatment was rendered that day which included spinal manipulation/ mobilization. Several days later the requested imaging reports were received and described the presence of an os odontoideum. CONCLUSION: In the presence of os odontoideum, familiarity with the signs and symptoms of potential cervical instability is imperative. Health care providers must remain diligent in their patient histories, physical exams, and imaging. This case highlights the importance of following up on imaging studies to rule out diagnoses that would involve treatment contraindications thus ensuring safe and effective treatment.

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)0.004
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.057
GPT teacher head0.361
Teacher spread0.304 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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