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Record W2946780243 · doi:10.18192/uojm.v9i1.4161

Medical Innovation Taking Form: 3D Printing at The Ottawa Hospital

2019· article· en· W2946780243 on OpenAlexaffvenueabout
Jonathan Whelan, Alexander J. Lingley, Olivier Miguel, Adnan Sheikh

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2019
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
Keywords3D printingOutreachMedicineMultitude3d printedHealth technologyMedical educationEngineering managementEngineeringHealth carePolitical scienceBiomedical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Three-Dimensional (3D) printing is an emerging medical technology with capacity to revolutionize multitude aspects of clinical care and medical education. This commentary highlights The Ottawa Hospital Medical 3D Printing Program, a leading Canadian site for the manufacturing of 3D-printed clinical solutions. In Ottawa, 3D printing has already been employed to optimize preoperative surgical planning, facilitate communication with patients, and enhance medical learning and outreach efforts. Rapid advances in manufacturing technology are poised to further expand current medical applications of 3D printing nation-wide.

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)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.295
Threshold uncertainty score0.586

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0060.003
Open science0.0030.002
Research integrity0.0210.011
Insufficient payload (model declined to judge)0.0580.010

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 head0.005
GPT teacher head0.201
Teacher spread0.196 · 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 designCase report
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
Published2019
Admission routes3
Has abstractyes

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