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Record W4382919139 · doi:10.1097/pxr.0000000000000249

Business practices efficiency: Impact of integrating digital technology on clinical P&O practices

2023· article· en· W4382919139 on OpenAlexaff
Arezoo Eshraghi, Clara Phillips, Winfried Heim

Bibliographic record

VenueProsthetics and Orthotics International · 2023
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsWest Park Healthcare Centre
Fundersnot available
KeywordsOrthoticsField (mathematics)Focus (optics)Reliability (semiconductor)Computer scienceBusinessManufacturing engineeringProcess managementMedicineEngineeringPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Additive manufacturing (AM) is on the path to transforming the approach to Prosthetics and Orthotics (P&O) manufacturing. Although digitalization of limbs and other body parts is not new to the field, it has not been widely accepted by the industry for various reasons. However, the reliability and precision that AM can attain, and the availability of various materials is improving rapidly. This professional opinion article discusses the ways that AM has changed P&O services, with a specific focus on prosthetic socket manufacturing. Digitalizing P&O services will eventually change the business model used in clinics, which is further explored here.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.049
GPT teacher head0.388
Teacher spread0.339 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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