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Record W3095572897 · doi:10.1055/s-0040-1717650

Das Augmented Reality Magic Mirror System - Anwendung einer Augmented Reality Technologie in der anatomischen Lehre

2020· article· de· W3095572897 on OpenAlexaff
AM von der Heide, Ina Seelbach, Felix Bork, Philipp Jutzi, Ming Meng, Pascal Fallavollita, Nassir Navab, Ekkehard Euler

Bibliographic record

VenueZeitschrift für Orthopädie und Unfallchirurgie · 2020
Typearticle
Languagede
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAugmented realityMAGIC (telescope)Computer scienceArtPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Fragestellung: Ziel der Studie ist die Analyse eines neuen Augmented Reality Magic Mirror Systems (ARMMS) zur anatomischen Wissensvermittlung am Beispiel der oberen Extremität im direkten Vergleich zum Lernmedium Anatomie Atlas (AA).

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.007
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0060.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0000.002

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 head0.053
GPT teacher head0.339
Teacher spread0.286 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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