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Record W1591715170 · doi:10.1007/978-1-59259-707-9

Neuroendocrinology in Physiology and Medicine

2000· book· en· W1591715170 on OpenAlexfundno aff
P. Michael Conn, Marc E. Freeman

Bibliographic record

VenueHumana Press eBooks · 2000
Typebook
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsnot available
FundersNovo NordiskMedical Research CouncilSemmelweis EgyetemUniversidade de São PauloUniversiteit UtrechtGeorgetown UniversityColorado State UniversityUniversity of PittsburghTulane UniversityInstitut National de la Recherche AgronomiqueUniversity of TorontoMichigan State UniversityCollege of Engineering, Michigan State UniversityF. Hoffmann-La RocheUniversity of PennsylvaniaUniversità degli Studi di BresciaNorthwestern UniversityFlorida State UniversityClemson UniversityPurdue University
KeywordsNeuroendocrinologyNeuroscienceEndocrine systemCognitive sciencePhysiologyMedicinePsychologyInternal medicineHormone

Abstract

fetched live from OpenAlex

The cover depicts a montage oftyrosine hydroxylase immunoreactive neurons labe led with fluorescent dye CY2 in the hypothalamic arcuate nucleus and their axon terminals in the median eminence.

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)0.000
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 score0.065
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0650.045

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 head0.046
GPT teacher head0.291
Teacher spread0.244 · 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

Citations148
Published2000
Admission routes1
Has abstractyes

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