Bibliographic record
Abstract
In this second edition of An Introduction to Neuroendocrinology , we have rewritten and greatly extended the original content. The revised text includes entirely new reference lists and a complete new set of illustrations. The book reflects the many advances that have occurred in the study of neuroendocrinology during the past 20 years. Nevertheless, and although the text is based largely on modern references, our primary aim is to provide an introductory description of mammalian neuroendocrine control systems. Several books are available that cover this topical and clinically relevant field, but, although valuable, these tend to be advanced texts of the edited, multi-author type. Our book is designed to provide the basic principles necessary to understand how the brain controls, and responds to, the endocrine hormones. It will be suitable for a variety of different students and especially those who might not have been previously exposed to a focused course in neuroendocrinology. Thus, students in psychology, biology and science should be able to master much of the basic material. However, the book is also highly appropriate for honors students and first-year graduate students in physiology, anatomy, neuroscience and medicine. This book is therefore designed for students in two levels of classes: introductory classes, in which all of the material will be new to the student, and more advanced classes, in which the students will be familiar with many of the terms and concepts through courses in biology, physiology, psychology or neuroscience, but who have not studied neuroendocrinology as an integrated discipline. This book offers an overall outline of the neuroendocrine system and will provide the vocabulary necessary to understand the interaction between hormones and the brain. In addition, we provide a concise description of those topics that must underpin any attempt to learn, and to teach, neuroendocrinology. For example, there are chapters on basic neuroscience (neurotransmitters and neuropeptides), the physiology of the endocrine glands (hormones), receptors and receptor signaling mechanisms (e.g. G proteins; nuclear receptors), hormone assay and gene expression techniques (e.g. ELISA; in situ hybridization) and a description of the immune system, with particular emphasis on the integration of immune and neuroendocrine pathways.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.399 | 0.300 |
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".