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Record W3124282083 · doi:10.1017/s1460396920001211

Technical illustration of Volumetric arc conformal radiotherapy planning in a case of paratesticular sarcoma

2021· article· en· W3124282083 on OpenAlexaff
Anil Gupta, Rambha Pandey, Seema Sharma, Vivek Ghosh, Ekta Dhamija, Adarsh Barwad, Sameer Rastogi, Rishabh Kumar, Rashi Kulshrestha

Bibliographic record

VenueJournal of Radiotherapy in Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineRadiation therapySpermatic cordRadiation treatment planningRadiologyInguinal canalSarcomaSurgeryPathologyInguinal hernia

Abstract

fetched live from OpenAlex

Abstract Introduction: Paratesticular sarcoma are extremely rare malignant tumours. Unlike other sites, they tend to be lower grade and have higher propensity of lymphatic spread. They tend to fail locally and occasionally in the regional lymph nodes. In the absence of target volume delineation guidelines and technical illustration of conformal planning, we have made an attempt to illustrate conformal planning methodology and define target volume based on current evidence in a case of paratesticular sarcoma. Methods: We are presenting a case of 62-year-old male who presented with 15-cm scrotal swelling and underwent high inguinal orchidectomy with ligation of spermatic cord. Histopathology presented a well-differentiated leiomyosarcoma of epididymis. Post-operative radiotherapy target volume included the tumour bed, ipsilateral inguinal nodes and lower pelvic nodes as the clinical target volume. Conclusion: Adjuvant radiotherapy using advanced delivery technique such as volumetric arc technique can provide good dose distribution with good sparing of organs at risk. The downside of conformal radiation delivery is that it is a resource-intensive and has no established target volume delineation guidelines.

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 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)0.001
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 score0.225
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.354
Teacher spread0.330 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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