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Record W4405287850 · doi:10.29173/eureka28836

Student Researcher Spotlight

2024· article· en· W4405287850 on OpenAlexaffvenue
Taylor Mytko

Bibliographic record

VenueEureka · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedical educationMathematics educationPsychologyMedicine

Abstract

fetched live from OpenAlex

Aryan and Taylor’s image, titled Mouse Radial Nerve in Cross-section, is featured on the back cover of the issue. The peripheral nervous system is composed of different axonal subpopulations that are responsible for carrying out information on essential processes such as pain, muscle contraction, and mechanoreception from the periphery to the brain. In this triple fluorescent image of the mouse Radial nerve in cross-section, each color represents a different axonal subpopulation. The red channel labels CHAT (Choline Acetyltransferase)+ motor axons which allow for skeletal muscle contraction in response to stimuli. The green channel labels CGRP (Calcitonin Gene Related Peptide)+ nociceptive (pain) axons which are responsible for a sustained release of inflammatory factors in response to tissue injury. The teal channel (Neurofilament 200) labels all the remaining proprioceptive and mechanoreceptive axonal subpopulations in the nerve. This image is the result of an immunohistochemistry protocol where a specific antibody with a fluorescent tag binds to the desired protein on the axon. This image, along with various images of different upper and lower limb nerves, allow us to quantify these subpopulations which may be critical for the development of future pain models and surgical interventions.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.356

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 head0.017
GPT teacher head0.332
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes2
Has abstractyes

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