MétaCan
Menu
Back to cohort
Record W4241162461 · doi:10.1373/clinchem.2013.209387

Commentary

2013· article· en· W4241162461 on OpenAlexaff
William E. Winter

Bibliographic record

VenueClinical Chemistry · 2013
Typearticle
Languageen
Field
Topic
Canadian institutionsJuvenile Diabetes Research Foundation
Fundersnot available
KeywordsMedicinePhilosophy

Abstract

fetched live from OpenAlex

Endocrine disorders can result from defects in hormone production, receptor binding, and postreceptor signaling. Concerning production, there can be an excess or a deficiency in a hormone, or a hormonopathy (e.g., an insulinopathy). In some hormonopathies, the defective hormone is not secreted but leads to apoptotic cell death and an absolute deficiency of the hormone (e.g., permanent neonatal diabetes caused by insulin gene mutations). Autoantibodies that act like hormone agonists can produce states of hyperfunction or hypofunction when acting as receptor antagonists. Autoantibodies that bind to other cell surface receptors can also alter hormone secretion (e.g., agonist autoantibodies directed against the parathyroid's calcium-sensing receptor). An altered ability to sense the environment can produce hormone deficiency (e.g., glucokinase mutations producing maturity-onset diabetes of the young 2). Defects in receptors or signaling typically lead to loss-of-function conditions (e.g., glucocorticoid, mineralocorticoid, or androgen resistance) although gain-of-function mutations do occur (e.g., testotoxicosis or the McCune–Albright syndrome). Receptor gain-of-function mutations allow an interface between the fields of endocrinology and oncology. Endocrine disorders can be due to defective entry of hormones into target tissues (e.g., monocarboxylate transporter 8 mutations). Hormone metabolism can also be disrupted, allowing increased receptor interaction (e.g., apparent mineralocorticoid excess). Defects in postreceptor signaling are extremely prevalent: The underlying disorder in most cases of type 2 diabetes is defective insulin signaling. The distribution of receptor subtypes among tissues can markedly affect the individual's phenotype (e.g., thyroid hormone β receptor vs. α receptor mutations). Lastly, mutations in genes controlling proteins regulated by hormones can produce clinical disease. Examples include nephrogenic diabetes insipidus from aquaporin 2 mutations, vitamin D–resistant rickets from SLC34A37 [solute carrier family 34 (sodium phosphate), member 3] mutations, and mutations in SCNN1B (sodium channel, non–voltage-gated 1, β subunit) or SCNN1G (sodium channel, non–voltage-gated 1, γ subunit) in Liddle syndrome. To maximally assist the clinician, the laboratorian must be aware of the huge variety of defects that can affect the endocrine system. solute carrier family 34 (sodium phosphate), member 3 sodium channel, non–voltage-gated 1, β subunit sodium channel, non–voltage-gated 1, γ subunit.

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)0.011
metaresearch head score (Gemma)0.107
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.086
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.107
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0070.005
Scholarly communication0.0080.004
Open science0.0060.005
Research integrity0.0860.059
Insufficient payload (model declined to judge)0.0450.029

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 head0.057
GPT teacher head0.383
Teacher spread0.326 · 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
GenreCommentary

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
Published2013
Admission routes1
Has abstractno

Explore more

Same venueClinical ChemistryFrench-language works237,207