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Record W1985981185 · doi:10.12927/whp.2013.23493

The Bone and Joint Decade (BJD) Initiative: How did Kuwait perform?

2013· article· en· W1985981185 on OpenAlexvenueno aff
Elham Hamdan, Fawzi F. Bouzubar, Michel D. Landry

Bibliographic record

VenueWorld health & population · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsJoint (building)Political scienceMedicineEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: The World Health Organization proclaimed the period between 2000 and 2010 as the Bone and Joint Decade (BJD). The BJD initiative set out to raise awareness regarding increasing incidence of musculoskeletal (MSK) conditions. The objective of this study was to assess the degree to which the BJD goals were met in Kuwait. METHODS: A gap analysis methodology was used to identify differences between the ideal state, defined as achieving the BJD goals, and the current state, defined as the extent to which BJD goals were achieved. RESULTS: Our gap analysis indicated that the majority of the BJD targets were not met in Kuwait; however, given the rising assumed incidence and prevalence of MSK disorders in Kuwait, it is critical to outline mechanisms for moving forward. CONCLUSIONS: The BJD goals are reachable in Kuwait. Attaining them requires a strong and sustainable commitment at many levels of government, provider organizations and the research community.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.285
Threshold uncertainty score0.567

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.024
GPT teacher head0.305
Teacher spread0.281 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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