MétaCan
Menu
Back to cohort
Record W2892268562 · doi:10.1002/dta.2500

Updated protocols for the detection of Sotatercept and Luspatercept in human serum

2018· article· en· W2892268562 on OpenAlexfundno aff
Christian Reichel, Günter Gmeiner, Katja Walpurgis, Mario Thevis

Bibliographic record

VenueDrug Testing and Analysis · 2018
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsBiotinylationAntibodyImmunoprecipitationAgarosePrimary and secondary antibodiesChemistryBlotChromatographyStreptavidinMolecular biologyComputer scienceBiochemistryBiotinImmunologyMedicineBiology

Abstract

fetched live from OpenAlex

We recently published two protocols for the detection of Sotatercept (ACE-011, ACVR2A-Fc) and Luspatercept (ACE-536, ACVR2B-Fc) in human serum. Both methods used covalently immobilized antibodies on agarose beads for immunoprecipitation and SAR-PAGE/Western blotting for detection. Disadvantages were the relatively high amount of antibody required per sample (10 μg) and the need of a secondary antibody for the final detection. The updated protocols overcome these limitations by antigen-antibody complex formation in solution followed by capture of the complex with anti-antibody-coated magnetic beads. They also omit the secondary antibody incubation step by usage of biotinylated primary antibodies, which can be directly incubated with streptavidin-HRP. Thus, the new protocols are faster, simpler, and cheaper and offer comparable sensitivities.

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)0.005
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: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.015

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 head0.027
GPT teacher head0.304
Teacher spread0.277 · 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
GenreProtocol

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

Citations13
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDrug Testing and AnalysisSame topicBlood groups and transfusionFrench-language works237,207