MétaCan
Menu
Back to cohort
Record W2020190200 · doi:10.17712/nsj.2015.2.20140621

Focal brainstem gliomas

2015· review· en· W2020190200 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeurosciences · 2015
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
FundersDeanship of Scientific Research, King Saud UniversityKing Fahad Medical CityKing Saud University
KeywordsNeuronavigationBrainstemMedicineGliomaRadiologyIntraoperative neurophysiological monitoringMagnetic resonance imagingSurgery

Abstract

fetched live from OpenAlex

Improved neuronavigation guidance as well as intraoperative imaging and neurophysiologic monitoring technologies have enhanced the ability of neurosurgeons to resect focal brainstem gliomas. In contrast, diffuse brainstem gliomas are considered to be inoperable lesions. This article is a continuation of an article that discussed brainstem glioma diagnostics, imaging, and classification. Here, we address open surgical treatment of and approaches to focal, dorsally exophytic, and cervicomedullary brainstem gliomas. Intraoperative neuronavigation, intraoperative neurophysiologic monitoring, as well as intraoperative imaging are discussed as adjunctive measures to help render these procedures safer, more acute, and closer to achieving surgical goals.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.173
GPT teacher head0.415
Teacher spread0.243 · 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