Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.639 | 0.471 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".