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Record W2512946126 · doi:10.1016/j.aogh.2016.04.506

Orthopedic care capacity assessment and strategic planning in Ghana: mapping a way forward

2016· article· en· W2512946126 on OpenAlexaff
Barclay T. Stewart, Adam Gyedu, Geoff Tansley, D. Yeboah, Forster Amponsah‐Manu, Charles Mock, Wilfred Labi-Addo, Robert Quansah

Bibliographic record

VenueAnnals of Global Health · 2016
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOrthopedic surgeryStrategic planningProcess managementBusinessOperations managementMedicineEngineeringMarketingSurgery

Abstract

fetched live from OpenAlex

75% case; 74% control), most patients (60% case response; 44% control response) report that they do not know the etiologies.About 50% of total participants report that they have no available resources for information about breast cancer.Other results reveal that participants occasionally or frequently have conversations about health and wellness with their family members (86% case response, 83% control response) and a self reported family history of cancer is comparable to that of the global percentage (8% case, 14% control).86% of cases have shared their breast cancer diagnosis with at least one family member.The Likert-Scale component reveals that both the cases and controls share similar sentiments about the perceptions of genetic risk and understanding family history.This denotes, that whether a woman is directly, indirectly, or not at all affected by breast cancer, it is the cultural contingencies that shape ones experience and interaction with breast cancer in Ibadan, Nigeria.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.077
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.163
GPT teacher head0.504
Teacher spread0.341 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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