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Record W2007788863 · doi:10.1097/iop.0000000000000465

A Novel Combination Point-of-View (POV) Action Camera Recording to Capture the Surgical Field and Instrument Ergonomics in Oculoplastic Surgery

2015· article· en· W2007788863 on OpenAlex
Kevin Warrian, Michael Ashenhurst, Adrian Gooi, Patrick Gooi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOphthalmic Plastic and Reconstructive Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of ManitobaUniversity of Calgary
Fundersnot available
KeywordsMedicinePoint (geometry)StereoscopyField (mathematics)Computer visionHead (geology)Field of viewComputer scienceArtificial intelligenceSurgery

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate a novel combination head-mounted/chest-mounted point-of-view recording system for oculoplastic surgical procedures. METHODS: The point-of-view head camera captures the surgical field, while the point-of-view chest camera captures a wide field of view to record instrument ergonomics. Various methods of recording were trialed. RESULTS: The head camera with a narrow field of view was better for recording fine details of the surgical field. The chest camera recording a wide field of view was optimal for recording hand positions. Stereoscopic recording of the instrument ergonomics was helpful in relaying the relative positions of the surgeon's hands and instruments. CONCLUSIONS: Point-of-view cameras are cost-effective means of recording oculoplastics procedures. The authors feel simultaneously recording the surgeon's ergonomics and the corresponding instrument movements within the surgical field, from the "surgeon's view", will augment surgical education.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.062
GPT teacher head0.289
Teacher spread0.227 · 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