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Record W4307221770 · doi:10.5281/zenodo.7249802

Antibody Characterization Report for TDP-43

2022· article· en· W4307221770 on OpenAlexaffabout
Donovan Worrall, Joël Ryan, Maryam Fotouhi, Riham Ayoubi, Wolfgang Reintsch, Thomas M. Durcan, Claire M. Brown, Peter S. McPherson, Carl Laflamme

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsAntibodyCharacterization (materials science)ChemistryMedicineMaterials scienceImmunologyNanotechnology

Abstract

fetched live from OpenAlex

A peer-reviewed antibody characterization article corresponding to this Zenodo preprint is openly available at F1000Research: https://doi.org/10.12688/f1000research.131852.2 Head-to-head comparison of available commercial antibodies against TDP-43 by immunoblot (Western blot), immunoprecipitation and immunofluorescence. The following study was funded in part by Genome Québec's Genomics Integration Program, awarded to the research laboratory of Peter S. McPherson. This work was supported by the ALS-Reproducible Antibody Platform (ALS-RAP), a public-private partnership established by three prominent ALS charities - the ALS Association (USA), the Motor Neurone Disease Association (UK), and the ALS Society of Canada.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.051
GPT teacher head0.313
Teacher spread0.262 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2022
Admission routes2
Has abstractyes

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