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Record W2158308032 · doi:10.1186/2045-709x-20-3

The role of chiropractic care in older adults

2012· article· en· W2158308032 on OpenAlexaff
Paul Dougherty, Cheryl Hawk, Debra K. Weiner, Brian J Gleberzon, Kari Andrew, Lisa Killinger

Bibliographic record

VenueChiropractic & Manual Therapies · 2012
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticMedicineGeriatricsPsychological interventionAlternative medicineRehabilitationGerontologyPopulationAcupuncturePopulation ageingMEDLINEFamily medicinePhysical therapyNursingPsychiatry

Abstract

fetched live from OpenAlex

There are a rising number of older adults; in the US alone nearly 20% of the population will be 65 or older by 2030. Chiropractic is one of the most frequently utilized types of complementary and alternative care by older adults, used by an estimated 5% of older adults in the U.S. annually. Chiropractic care involves many different types of interventions, including preventive strategies. This commentary by experts in the field of geriatrics, discusses the evidence for the use of spinal manipulative therapy, acupuncture, nutritional counseling and fall prevention strategies as delivered by doctors of chiropractic. Given the utilization of chiropractic services by the older adult, it is imperative that providers be familiar with the evidence for and the prudent use of different management strategies for older adults.

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)0.004
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.295
Teacher spread0.286 · 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

Citations33
Published2012
Admission routes1
Has abstractyes

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