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Primary Bone Tumors in Children and Adolescents Treated at a Referral Center in Northern Tanzania

2019· article· en· W2981361303 on OpenAlexaff
Michelle Ghert, Winfrida C. Mwita, Faiton Ndesanjo Mandari

Bibliographic record

VenueJAAOS Global Research and Reviews · 2019
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineTanzaniaReferralOsteosarcomaSarcomaHumerusPediatricsTibiaGeneral surgerySurgeryFamily medicinePathology

Abstract

fetched live from OpenAlex

Bone tumors account for a small fraction of childhood cancers. Most published reports are from developed countries. The purpose of this study was to review the primary bone tumors in children and adolescents treated at a referral center in Northern Tanzania. We completed a 10-year hospital-based cross-sectional study in which all patients younger than 20 years diagnosed with a primary bone tumor at the Kilimanjaro Christian Medical Center Orthopaedic Department from January 2006 to December 2015 were identified and reviewed. Of the 80 identified patients, 15 (18.8%) were aged 5 to 8 years, and 65 (81%) were aged 9 to 19 years. Forty-seven males (59%) and 33 females (41%) were identified. The most common tumor locations were the femur, tibia, and humerus. Osteosarcoma was the most common malignant diagnosis (49 patients, 61%). No cases of Ewing sarcoma were reported. The most common tribal origins of the patients were Chagga and Maasai. Most primary bone tumors treated at a referral center in Northern Tanzania are malignant, with osteosarcoma representing the vast majority. No cases of Ewing sarcoma were identified in this tertiary referral hospital-based database.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.350
Teacher spread0.309 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2019
Admission routes1
Has abstractyes

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