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Record W2199720786

Validation of EP1 Antibody Clone for Estrogen Receptor Immunohistochemistry for Breast Cancer.

2016· article· en· W2199720786 on OpenAlexaff
Caroline Diorio, Daniela Furrer, Sophie Laberge, Ion Popa, Simon Jacob, Louise Provencher, Jean‐Charles Hogue

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBreast cancerImmunohistochemistryTissue microarrayEstrogen receptorclone (Java method)AntibodyCancerKappaMedicinePopulationConfidence intervalInternal medicineOncologyBiologyImmunologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: SP1 Rabbit monoclonal antibody to estrogen receptor (ER) has long been the standard for determination of ER status in breast cancer but has been replaced by the rabbit EP1 clone. AIM: To validate the EP1 antibody clone for use in determination of breast cancer ER status in a large clinical population against the previous standard SP1. MATERIALS AND METHODS: ER immunohistochemistry was assessed in 523 consecutive cases from a clinical setting using tissue microarrays. RESULTS: The kappa statistic showed that the agreement of ER status between SP1 and EP1 was considered to be almost perfect (kappa=0.97, 95% confidence interval=0.94-1.00). Sensitivity was 99.3%, specificity was 98.6% and overall agreement was 99.2%. CONCLUSION: The EP1 antibody was herein validated regarding its use in breast cancer with almost perfect agreement with the previously used standard SP1 antibody.

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)0.006
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicEstrogen and related hormone effects→French-language works237,207→