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Record W2095352518 · doi:10.1097/mrr.0b013e32834df622

Screening for scoliosis

2011· review· en· W2095352518 on OpenAlexaboutno aff
Maciej Płaszewski, Roman Nowobilski, Paweł Kowalski, Maciej Cieśliński

Bibliographic record

VenueInternational Journal of Rehabilitation Research · 2011
Typereview
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsnot available
FundersBritish Orthopaedic Association
KeywordsGrading (engineering)MedicineMEDLINEScoliosisCochrane LibraryFeelingEvidence-based medicineFamily medicinePhysical therapyAlternative medicinePsychiatryPsychologySocial psychologyPathology

Abstract

fetched live from OpenAlex

Idiopathic scoliosis affects 2-3% of adolescents. Large, progressing deformities, mostly present in girls, may lead to pulmonary complications, pain symptoms, the feeling of social isolation, and even mental disorders. The correlation of screening programs with surgery rate reduction and the clinical effectiveness of bracing remain a matter of debate. Critics indicate overdetection, qualification for therapy of insignificant curves, unjustified treatment, and risks of psychological side effects, whereas supporters underline the need for screening, and suggest improvements. It remains unclear whether such opposite opinions are based on sound evidence. To identify relevant studies, guidelines, and recommendations, MEDLINE, Google Scholar, and Cochrane Library databases were searched. The levels of evidence presented in selected studies and grading of recommendations reported in available guidelines and recommendation statements were assessed using the SIGN scoring system. Screening programs are legislated, recommended, or not recommended in different American states. British and Canadian screening recommendations do not mention scoliosis; Australian boards recommend against scoliosis screening programs. Other publications such as Singapore, Turkish, and Malaysian publications underline the cost-effectiveness and clinical importance of the procedures. Different Greek authors postulate the benefits and harms caused by the programs to many schoolchildren. Such a polarity illustrates the topicality of the quality of scientific evidence analyses and the significance of the grading of the recommendations process. It appears that critical opinions often result from implementing such analyses, whereas those supporting the programs tend to value the importance of expert opinions.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.450
GPT teacher head0.593
Teacher spread0.143 · 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 designOther design
Domainnot available
GenreReview

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

Citations31
Published2011
Admission routes1
Has abstractyes

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