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Record W2096755293 · doi:10.1109/tbme.2012.2182995

Three-Dimensional Rotation of Mouse Embryos

2012· article· en· W2096755293 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

VenueIEEE Transactions on Biomedical Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRotation (mathematics)EmbryoPhysicsComputer scienceArtificial intelligenceBiologyCell biology

Abstract

fetched live from OpenAlex

Research and clinical applications, such as microinjection and polar-body biopsy involve 3-D rotation of mammalian oocytes/embryos. In these cell manipulation tasks, the polar body of an embryo/oocyte must be made visible and properly oriented under optical microscopy. Cell rotation in conventional manual operation by skilled professionals is based on trial and error, such as through repeated vacuum aspiration and release. The randomness of this manual procedure, its poor reproducibility, and inconsistency across operators entail a systematic technique for automated, noninvasive, 3-D rotational control of single cells. This paper reports a system that tracks the polar body of mouse embryos in real time and controls multiple motion control devices to conduct automated 3-D rotational control of mouse embryos. Experimental results demonstrated the system's capability for polar-body orientation with a high success rate of 90%, an accuracy of 1.9 °, and an average speed of 22.8 s/cell (versus averagely 40 s/cell in manual operation).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score0.585

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 head0.011
GPT teacher head0.201
Teacher spread0.190 · 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