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Record W7096602659

IRMA and RIA Compared for Assessing Dexamethasone Suppression of Corticotropln in Plasma, Alex M. Sharp,

2016· article· en· W7096602659 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAdrenal Hormones and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsRadioimmunoassayDexamethasoneAntibodyAdrenal glandHydrocortisoneSecretionAdrenocorticotropic hormone
DOInot available

Abstract

fetched live from OpenAlex

Dexamethasone (DM8) suppresses secretion of corti-cotropin (ACTH) by the pituitary gland and hence also suppresses cortisol production by the adrenal gland, an overnight dose of 1 mg being sufficient to suppress the pituitary-adrenal axis (1). The availability of a immuno-radiometric assay (IRMA) kit for ACTH from Nichols Insti-tute (San Juan Capistrano, CA 92675) prompted us to compare it with our in-house radioimmunoassay (RIA) for ACTH, with respect to its ability to detect ACTH suppres-sion. Our ACTH RIA uses an antibody from IgG Corp. (Nashville, TN 37211), a standard from Peninsular Labs. (Belmont, CA 94002), an ‘251-tracer from CIS (Sarclay, France), and a second antibody from Bio-R[A (Montreal, Canada H3M 3A2). To measure cortisol suppression, we used the RIA kit from Farmos (Turku, Finland), which measures cortisol directly in both plasma and urine. Plasma DM8 was measured by an in-house RIA with use of an antibody from Professor V#{233}csei(D partment of Pharma-

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.011

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 head0.033
GPT teacher head0.320
Teacher spread0.286 · 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 designBench or experimental
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

Citations0
Published2016
Admission routes1
Has abstractyes

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