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Record W2950859087 · doi:10.1002/ar.24189

Cajal's Interactions with Sherrington and the Croonian Lecture

2019· article· en· W2950859087 on OpenAlexfundno aff
Juan Carlos, Zoltán Molnár

Bibliographic record

VenueThe Anatomical Record · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research Council CanadaWellcome Trust
KeywordsNeuroscienceInterstitial cell of CajalObituaryFriendshipPhilosophyPsychologyMedicineSmooth muscleInternal medicineTheology

Abstract

fetched live from OpenAlex

Sherrington was a major proponent of the neuron doctrine and he was inspired by Santiago Ramón y Cajal's theory of dynamic polarization of nerve cells (Ley de la polarización dinámica de la célula nerviosa). Sherrington coined the term "synapse" to name the Cajal description of interneuronal contact and he gave the term, for functional nerve endings, as "Boutons terminaux," still used today. These two giants of neuroscience met only once, but they had a life-long friendship. It was Sherrington who wrote Cajal's Obituary for the Royal Society. We review here some of the scientific exchanges between Cajal and Sherrington, with particular attention to 1894, when the two neuroscientist met in London during Cajal's visit to deliver the Croonian Lecture to the Royal Society. We shall examine not only the scientific exchanges but also their friendship, which was immediate and strong. Anat Rec, 303:1181-1188, 2020. © 2019 American Association for Anatomy.

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)0.005
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0050.007
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0030.010
Insufficient payload (model declined to judge)0.0100.004

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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
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

Citations8
Published2019
Admission routes1
Has abstractyes

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