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Record W2801362673 · doi:10.1089/soro.2017.0072

A Dynamic Compliance Cervix Phantom Robot for Latent Labor Simulation

2018· article· en· W2801362673 on OpenAlex

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

VenueSoft Robotics · 2018
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsYork UniversityMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsImaging phantomCervixRobotComputer scienceSoft palateMechatronicsArtificial intelligenceSimulationMedicineMedical physicsSurgeryRadiology

Abstract

fetched live from OpenAlex

Physical simulation systems are commonly used in training of midwifery and obstetrics students, but none of these systems offers a dynamic compliance aspect that would make them more truly representative of cervix ripening. In this study, we introduce a unique soft robot phantom that simulates the cervix softening during the latent labor phase of birth. This proof-of-concept robotic phantom can be dilated by 1 cm and effaced by 35% through the application of a Foley catheter-like loading mechanism. Furthermore, psychophysics trials demonstrate how untrained subjects can identify hard and soft states of the phantom with specificities of 91% and 87%, respectively. Both results indicated the appropriateness for application of this soft robot technology to birth training simulators.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.085
GPT teacher head0.377
Teacher spread0.292 · 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