MétaCan
Menu
Back to cohort
Record W4401715027 · doi:10.1080/0964704x.2024.2383186

Ghost cells: Wilder Penfield and the characterization of glia and glial pathology, 1924–1932

2024· article· en· W4401715027 on OpenAlexaffabout
Adam M.R. Groh, Richard Leblanc

Bibliographic record

VenueJournal of the History of the Neurosciences · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsNeuropathologyMicrogliaPathologyMyelinEpilepsyNeuroscienceNeurogliaAstrocytePathologicalCentral nervous systemBiologyMedicineImmunologyInflammation

Abstract

fetched live from OpenAlex

Wilder Penfield is known for his contributions to the structure-function relationship of the brain and for the surgical treatment of focal epilepsy. Less well known are his contributions to the study of glial cells and his investigation of their role in human neuropathology. Penfield learned the gold and silver methods for staining neurons, glial cells, and their projections from Charles Sherrington and Pío del Río-Hortega. He and his colleague William Cone established a laboratory for the study of glial cells and human neuropathology using metallic stains, initially at the Presbyterian Hospital in New York City in 1925, and then at the Montreal Neurological Institute in 1928. Penfield, Cone, and their research fellows, building on the findings of Río-Hortega, confirmed the existence of oligodendrocytes and their relationship with myelin, and investigated the putative mesodermal origin of microglia. They discovered the reaction of oligodendrocytes to pathological stressors, and the phagocytic activity of microglia in human gliomas. In this article, we argue that Penfield's studies of astrocytes, oligodendrocytes, and microglia, and their responses to craniocerebral trauma, epilepsy, malignant brain tumors, and other pathologies of the central nervous system inaugurated a new era in clinical neurocytology and neuropathology.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0020.010
Scholarly communication0.0030.007
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.214
Teacher spread0.194 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the History of the NeurosciencesSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207