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Record W2561329233 · doi:10.5959/eimj.v8i4.458

The 3 D Printing Age and Basic Sciences Education

2016· article· en· W2561329233 on OpenAlexafffundabout
Safaa El Bialy

Bibliographic record

VenueEducation in Medicine Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsPsychologyMathematics educationGerontologyMedicine

Abstract

fetched live from OpenAlex

Acquiring teaching resources is challenging for many medical schools, in particular the acquisition of cadavers for anatomy labs. Cadavers are not easy to store, and are costly to maintain. With threedimensional (3 D) printing, one can create nonperishable anatomy specimens that will overcome some of those challenges. For the purpose of teaching human anatomy at University of Ottawa, highly realistic 3 D printed models (heart, kidney and gastrointestinal system) were created. Images in stereolithography (STL) format were downloaded for free from Thingverse community and printed using Makerbot replicator 2 X machines, using the makerspace facility, Faculty of Engineering, University of Ottawa. The primary advantage of this technique is its ability to create almost any shape or geometric feature. Unlike cadavers, 3 D printed models will not deteriorate so they are also cost effective. This technological development is becoming more and more popular. Eventually, it will impact every single aspect of our lives.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.106

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.299
Teacher spread0.290 · 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 designOther design
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

Citations3
Published2016
Admission routes3
Has abstractyes

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