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Record W2058429220 · doi:10.1001/archsurg.138.8.832

T1a breast carcinoma and the role of axillary dissection

2003· article· en· W2058429220 on OpenAlex

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.

Bibliographic record

VenueArchives of Surgery · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLymphovascular invasionMedicineBreast cancerAxillary DissectionAxillary Lymph Node DissectionCarcinomaSurgeryInternal medicineOncologyCancerRadiologyMetastasisMastectomySentinel lymph node

Abstract

fetched live from OpenAlex

HYPOTHESIS: Axillary dissection (AD) does not affect recurrence or survival in T1a breast cancer. DESIGN: Cohort study comparing patients who underwent AD and those who did not. SETTING: Provincial cancer agency. PATIENTS: Six hundred ninety-one women with pathologically diagnosed T1a tumors. MAIN OUTCOME MEASURES: Rates of axillary metastases stratified according to grade and lymphovascular and/or neural invasion, rates of relapse, and disease-specific survival. RESULTS: Grade 1, 2, and 3 tumors without lymphovascular and/or neural invasion had axillary nodal involvement rates of 0.7%, 7%, and 7.8% of patients, respectively; with lymphovascular and/or neural invasion, axillary nodes were involved in 9.1%, 39.3%, and 44.4%, respectively. No statistically significant differences were found between the cohorts in relapse rates (P =.70) or survival (P =.84). CONCLUSION: Higher tumor grade and lymphovascular and/or neural invasion increased the rate of nodal metastases in T1a tumors, but AD did not improve relapse rates or breast cancer-specific survival.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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