Neuronal classes and their specialization in the corticoid complex of a food-storing bird, the Indian House Crow (<i>Corvus splendens</i>)
Bibliographic record
Abstract
Neuronal classes and their specialization in the corticoid complex of a food-storing bird (the Indian House Crow, Corvus splendens Vieillot, 1817) have been investigated using Golgi and Cresyl-violet methods. The aim of present study is to observe the neuronal characteristics of corticoid complex of the House Crow (food-storing bird) and to compare them with that of a nonfood-storing bird (the Strawberry Finch, Estrilda amandava = Amandava amandava (L., 1758)). Three main neuronal classes, viz. projection neurons, local circuit neurons, and stellate neurons, have been identified in both intermediate corticoid area (CI) and dorsolateral corticoid area (CDL) based on soma shape, arrangement of dendrites around the soma, and axonal projection. Projection neurons have four neuronal subtypes: multipolar, pyramidal, pyramidal-like, and horizontal cells. It seems that the specialization in pyramidal, local circuit, and pyramidal-like neurons show advantages in the House Crow as a food-storing bird for better memory, cognition, and connectivity in corticoid complex. This is the first study of its kind that provides information regarding neuronal classes within the corticoid complex of a food-storing bird and a comparison between a food-storing bird (House Crow) and the only available study on a nonfood-storing bird (Strawberry Finch).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".