MétaCan
Menu
Back to cohort
Record W2024536834 · doi:10.1055/s-2008-1073132

Day Surgery Awake Craniotomy for Removing Brain Tumours: Technical Note Describing a Simple Protocol

2008· review· en· W2024536834 on OpenAlexaffabout
Giorgio Carrabba, Lashmi Venkatraghavan, Mark Bernstein

Bibliographic record

Venuemin - Minimally Invasive Neurosurgery · 2008
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineAwake craniotomyCraniotomyNeurosurgeryProtocol (science)SurgerySimple (philosophy)CohortGeneral surgeryAlternative medicine

Abstract

fetched live from OpenAlex

Day surgery awake craniotomy has been recently proposed for patients harbouring supratentorial brain tumours. This technique has been demonstrated to be safe and effective in a large cohort of patients operated by one neurosurgeon at the University of Toronto. The aim of this paper is to present a technical description of the protocol that has been adopted for these patients and a discussion of relevant practical issues which may arise. In particular, patient eligibility criteria are briefly discussed and intra- and post-operative management are presented. Key messages for those who are going to start to perform day surgery awake craniotomies include the preparation of a fast, simple and standardized protocol for the treatment of these patients and cooperation among patients and their care-givers (surgeon, anesthetist, nurses, family members).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.004

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.

Opus teacher head0.116
GPT teacher head0.355
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations64
Published2008
Admission routes2
Has abstractyes

Explore more

Same venuemin - Minimally Invasive NeurosurgerySame topicGlioma Diagnosis and TreatmentFrench-language works237,207