The effect of a static magnetic field on the morphometric characteristics of neurosecretory neurons and<i>corpora allata</i>in the pupae of yellow mealworm<i>Tenebrio molitor</i>(Tenebrionidae)
Bibliographic record
Abstract
PURPOSE: The morphometric characteristics of A1 and A2 protocerebral neurosecretory neurons (cell and nuclei size, number of nucleoli in the nuclei); corpora allata size, nuclei size, cell number, were investigated in the pupae of yellow mealworm, Tenebrio molitor (L.), exposed to a strong static magnetic field of 320 mT maximum induction (10,000 times higher than the Earth's). MATERIALS AND METHODS: The experimental groups of Tenebrio molitor pupae were: A control group exposed only to natural magnetic field and sacrificed at the eighth day of pupal development (C); and pupae kept in a strong static magnetic field for eight days and then sacrificed (MF). Serial brain cross-sections were stained using the Alcian Blue Floxin technique. All the parameters were analyzed and measurements were performed using an image processing and analysis system (Leica, Cambridge, UK) linked to a Leica DMLB light microscope (program is QWin - Leica's Quantimet Windows-based image analysis tool kit). RESULTS: The values of morphometric parameters of neurosecretory neurons and corpora allata were significantly increased after exposure of the pupae to the strong magnetic field. CONCLUSIONS: The strong magnetic field influence characteristics of protocerebral neurosecretory neurons and corpora allata in the late Tenebrio molitor pupae.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".