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Record W2513036042 · doi:10.21873/anticanres.11017

Tissue Microarray Is a Reliable Tool for the Evaluation of HER2 Amplification in Breast Cancer

2016· article· en· W2513036042 on OpenAlex
Daniela Furrer, Simon Jacob, Chantal Caron, François Sanschagrin, Louise Provencher, Caroline Diorio

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnticancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsHôpital du Saint-SacrementUniversité Laval
FundersFonds de Recherche du Québec - SantéFondation du cancer du sein du QuébecUniversité Laval
KeywordsConcordanceTissue microarrayBreast cancerFluorescence in situ hybridizationGene duplicationOncologyPathologyCancerMicroarrayMedicineBiopsyInternal medicineBiologyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

AIM: We examined an economical method for evaluating the amplification of the human epidermal growth factor receptor 2 (HER2) gene in breast cancer specimens. MATERIALS AND METHODS: We compared HER2 amplification determined by fluorescence in situ hybridization (FISH) on whole-tissue (WT) blocks used for diagnostic and on tissue microarray (TMA) sections for a cohort of 521 consecutive patients with breast cancer. In a subset of 116 patients, we examined HER2 concordance from the WT section and a TMA section from a randomly chosen additional block (a proxy of the core biopsy). RESULTS: Overall concordance for HER2 amplification between WT and TMA sections was 98.2%, and between sections from WT and from the additional block was 99.0%. CONCLUSION: The high concordance rates support the use of TMA for the evaluation of HER2 amplification in breast cancer and suggest that FISH can be used to assess HER2 using core biopsies.

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.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.237
GPT teacher head0.540
Teacher spread0.302 · 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