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Record W2974031124 · doi:10.7759/cureus.5706

Novel Uses of Radioactive Seeds in Surgical Oncology: A Case Series

2019· article· en· W2974031124 on OpenAlexaff
Michèle Beniey, Kerianne Boulva, Ahmad Kaviani, Érica Patocskai

Bibliographic record

VenueCureus · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineAxillaRadioactive iodineBreast cancerMelanomaLymph nodeCancerAxillary lymph nodesBasal cellRadiologySurgical oncologyLymphOncologyInternal medicinePathologyCancer researchThyroid

Abstract

fetched live from OpenAlex

The localization of nonpalpable axillary metastatic lymph nodes has been achieved using several techniques in the past. Amongst these techniques, the use of radioactive iodine seeds is increasingly spread, and was initially reserved to breast-conserving surgery. Many studies have assessed the use of radioactive seed localization for the surgical management of breast cancer patients diagnosed with lymph node metastases. However, few articles have reported their utilization in other cancer subtypes and in complex clinical situations. This case series describes the innovative use of radioactive seeds in the axilla in five patients, including one case of squamous cell carcinoma skin cancer, one case of malignant melanoma, and three cases of invasive breast cancer.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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 designCase report
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
Published2019
Admission routes1
Has abstractyes

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