MétaCan
Menu
Back to cohort
Record W4401462853 · doi:10.6000/1929-5995.2024.13.06

Polymers used in Vertebroplasty: The Importance of Material Technology in the Rehabilitation of Osteoporotic Patients

2024· article· en· W4401462853 on OpenAlexvenueno aff
Daniela Gallon Corrêa, Jonas Lenzi De Araújo, Harrison Lourenço Corrêa

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2024
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoporosisQuality of life (healthcare)RehabilitationLife qualityHuman lifePopulation ageingLongevityMedicineForensic engineeringPopulationMaterials scienceRisk analysis (engineering)Physical therapyEngineeringGerontologyEnvironmental healthNursingInternal medicine

Abstract

fetched live from OpenAlex

Recent statistics show that the human population is tending towards aging. More effective medications and medical-hospital treatments, a more balanced diet, and regular physical activities contribute to longevity with quality of life.However, on many occasions, the natural aging process brings with it some chronic diseases, such as osteoporosis. Characterized by the loss of bone density, it can compromise mobility and even lead to death due to vertebral fractures, among other issues.To mitigate these risks, materials engineering becomes useful for restoring partial and/or total bone structure. In combination with a physiotherapeutic approach, they can rehabilitate the patient, providing them with a better quality of life.The present work aims to discuss the main polymeric materials used for the treatment of osteoporosis in patients with fractures.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.012
GPT teacher head0.301
Teacher spread0.289 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Research Updates in Polymer ScienceSame topicBone Tissue Engineering MaterialsFrench-language works237,207