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Record W1987811922 · doi:10.3138/jvme.30.1.73

Use of Animation-Enhanced Video Clips for Teaching Abnormal Breathing Patterns

2003· article· en· W1987811922 on OpenAlexvenueno aff
Eleanor C. Hawkins, Bernie Hansen, Brenda L. Bunch

Bibliographic record

VenueJournal of Veterinary Medical Education · 2003
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCLIPSMedicineAnimationBreathingVideotape RecordingMultimediaAnesthesiaSurgeryComputer science

Abstract

fetched live from OpenAlex

The ability to characterize disease of the respiratory tract accurately based on breathing pattern is helpful for the development of differential diagnoses and an efficient diagnostic plan and critical for the stabilization of patients in respiratory distress. Veterinary students do not have sufficient clinical experience to observe personally all types of respiratory diseases and their resultant abnormal breathing patterns. We developed a teaching tool, the animated breathing pattern videotape (ABV), to fill this gap. The ABV is a collection of video clips of small animal patients with normal and abnormal breathing patterns on a conventional videotape of approximately 20 minutes duration. Each video clip is shown for 20 to 40 seconds, followed by the same clip with superimposed animation of rib and diaphragm motion, followed by the initial clip again, without overlying animation. The ABV has since been used in teaching third-year veterinary students, interns, residents, practicing veterinarians, and veterinary technicians. Student evaluations and responses to questionnaires by interns, residents, practicing veterinarians, veterinary technicians, and peer reviewers have been uniformly positive.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.368
GPT teacher head0.537
Teacher spread0.168 · 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.

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

Citations9
Published2003
Admission routes1
Has abstractyes

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