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<scp>J</scp> oseph <scp>E</scp> rlanger (1874–1965)

2015· other· en· W1487523295 on OpenAlexaff
Alan J. McComas

Bibliographic record

VenueEncyclopedia of Life Sciences · 2015
Typeother
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPresidencyNerve cellsPhysiologyNeuroscienceMedicinePsychologyCognitive science

Abstract

fetched live from OpenAlex

Abstract Joseph Erlanger was awarded the Nobel Prize for Medicine or Physiology in 1944, and shared it with Herbert Gasser for research on the nerve impulse. They were the first to employ a cathode ray tube and thereby to obtain accurate recordings of the impulses (action potentials) in groups of vertebrate nerve fibres; later, Erlanger was able to record from single fibres. At the time of receiving the award Erlanger, who also had a strong background in cardiovascular physiology, was the Head of the Physiology Department at Washington University, St Louis. Erlanger's many honours included the Presidency of the American Physiological Society (1926 –1929).

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1050.045

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 head0.038
GPT teacher head0.272
Teacher spread0.234 · 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
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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