Bibliographic record
Abstract
This new edition of Neurosurgery: The Essential Guide to the Oral and Clinical Neurosurgical Exam provides a concise and practical guidebook of the core knowledge and principles for the International and Intercollegiate FRCS Specialty Examination in Neurosurgery. It is a vital resource for the American Board of Neurological Surgery (ABNS) and other neurosurgical examinations around the world. Written by neurosurgeons at the top of their field and based on new guidelines, this book takes students through how to succeed in the FRCS neurosurgery exams and provides an overview of crucial short and intermediate cases designed to mirror the exam’s testing of a candidate’s clinical knowledge, diagnostic acumen, investigation and interpretation, treatment options and taking consent. Including 72 vital online revision flash cards, covering critical and diverse examination cases from trauma to paediatric spine exams, this edition also contains crucial guidance to Vivas on the following: Operative surgery and surgical anatomy Investigation of the neurosurgical patient The non-operative clinical practice of neurosurgery This book is a must-read for candidates preparing for the final Intercollegiate Specialty Examination in Neurosurgery (UK), International FRCS Specialty Examination in Neurosurgery (UK) International FRCS Specialty Examination in Neurosurgery as well as the American, Canadian, European and Australasian exams. In addition to helping candidates pass their final exams, the book provides wonderful insight into Neurosurgery for Medical Students, Surgical Residents and Neurosurgical Consultants.
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 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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.032 |
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; both teacher heads 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".