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Laparoscopic Adrenal Surgery for Giant Ganglioneuroma

2015· article· en· W2150192183 on OpenAlexvenueno aff
Bruno Costa do Prado, Marcelo Cabral Lamy de Miranda, Márcio Maia Lamy de Miranda, Aníbal Wood Branco

Bibliographic record

VenueJournal of cancer research updates · 2015
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsnot available
Fundersnot available
KeywordsGanglioneuromaMedicineAsymptomaticAbdomenLesionMagnetic resonance imagingLaparoscopyAbdominal ultrasonographyLaparoscopic surgeryRadiologyAdrenal glandSurgeryComputed tomographyNeuroblastomaPathology

Abstract

fetched live from OpenAlex

We present herein a case of a 24-year-old woman with incidentally diagnosed right adrenal ganglioneuroma with 14cm in size that was removed completely by the laparoscopic approach. The patient was asymptomatic and the tumor was first diagnosed on abdominal ultrasonography. A subsequent computed tomography (CT) of the abdomen confirmed a 12x 11x9cm complex expansive mass of right adrenal, with well-defined outlines. Magnetic resonance imaging (MRI) showed a solid lesion measuring 11 x 9 x 11cm arising from the right adrenal. Laparoscopic complete excision of the mass was accomplished through a transabdominal lateral approach. The surgical specimen weighed 665 g and 14 x 10 x 7 cm in size. There was no complication in postoperative period, and the patient was released from the hospital two days after the operation. The patient resumed her normal activities in one week. Histology was consistent with an adrenal ganglioneuroma. A control CT was made one year after the surgery with no evidence of lesion suggestive of relapse. Adrenal ganglioneuromas are rare lesions with a benign behavior in which surgery is the only possible form of treatment. In centers of advanced laparoscopy this method of access can be used, even for larger lesions.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.176
GPT teacher head0.446
Teacher spread0.270 · 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 designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

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