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Rethinking of osteoporosis through a sex- and gender-informed approach in the COVID-19 era

2021· article· en· W3184097237 on OpenAlexaff

Bibliographic record

VenueMinerva Obstetrics and Gynecology · 2021
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOsteoporosisGeneralizability theoryPsychological interventionNarrative reviewDiseaseClinical trialLimiting

Abstract

fetched live from OpenAlex

Standards and models of reference for osteoporosis (OP) have been developed for female individuals as they are more likely to be affected by the disease. Nonetheless, OP is also responsible for one-third of hip fractures in male individuals suggesting that a sex-blinded approach to OP may lead to miss opportunities for equity in bone health. OP-related fractures, especially hip fractures, are a matter of immediate concern as they are associated with limited mobility, chronic disability, loss of independence, and reduced quality of life in both sexes. When it comes to sociocultural gender, the effect of gender domains (i.e., identity, roles, relations, and institutionalized gender) on development and management of OP is largely overlooked despite risk factors or protective conditions are gendered. Clinical trials testing the efficacy and safety of anti-OP drugs as well as non-pharmacological interventions have been conducted mainly in female participants, limiting the generalizability of the findings. The present narrative review deals with the sex and gender-based challenges and drawbacks in OP knowledge and translation to clinical practice, also considering the impact of coronavirus disease 2019 pandemic.

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)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.107
GPT teacher head0.357
Teacher spread0.249 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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