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Record W2112441719 · doi:10.1302/0301-620x.83b8.12028

Classification of positive margins after resection of soft-tissue sarcoma of the limb predicts the risk of local recurrence

2001· article· en· W2112441719 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

VenueJournal of Bone and Joint Surgery - British Volume · 2001
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsToronto Rehabilitation InstitutePrincess Margaret Cancer CentreMount Sinai Hospital
Fundersnot available
KeywordsSoft tissue sarcomaMedicineSoft tissueResectionSarcomaRadiologySurgeryPathology

Abstract

fetched live from OpenAlex

We considered whether a positive margin occurring after resection of a soft-tissue sarcoma of a limb would affect the incidence of local recurrence. Patients with low-grade liposarcomas were expected to be a low-risk group as were those who had positive margins planned before surgery to preserve critical structures. Two groups, however, were expected to be at a higher risk, namely, patients who had undergone unplanned excision elsewhere with a positive margin on re-excision and those with unplanned positive margins occurring during primary resection. Of 566 patients in a prospective database, 87 with positive margins after limb-sparing surgery and adjuvant radiotherapy were grouped according to the clinical scenario by an observer blinded to the outcome. The rate of local recurrence differed significantly between the two low- (4.2% and 3.6%) and the two high-risk groups (31.6% and 37.5%). This classification therefore provides useful information about the incidence of local recurrence after positive-margin resection.

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)0.001
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 score0.074
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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