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Record W1982427992 · doi:10.1159/000367659

Laparoendoscopic Single-Site Surgery for Benign Ovarian Cystectomies

2015· article· en· W1982427992 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

VenueGynecologic and Obstetric Investigation · 2015
Typearticle
Languageen
FieldMedicine
TopicMinimally Invasive Surgical Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineLaparoscopyCosmesisCystectomySurgeryGroup BBlood lossUrologyInternal medicineBladder cancerCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Single-port laparoscopy (LESS) utilizes a single, multichannel port in an attempt to decrease postoperative pain, while enhancing cosmesis and minimizing the potential risks and morbidities associated with the multiple ports used in conventional laparoscopy. METHODS: We performed a retrospective study examining three tertiary care referral centers. From September 2009 until March 2013, 31 patients with ovarian cystic lesions were treated using the LESS technique. A control group of 57 patients who underwent conventional laparoscopic ovarian cystectomy was included for comparison. RESULTS: All patients underwent a technically successful cystectomy. There were no statistically significant differences in the mean operative time or estimated blood loss between the two groups. Narcotic use during the recovery period was reported in less patients in the LESS group than in the laparoscopic group (p = 0.05). CONCLUSIONS: The LESS technique can be used to safely perform cystectomies on women with benign ovarian cysts. Additional investigation is needed to evaluate the safety, cost-effectiveness and long-term outcomes of this new approach.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
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 head0.107
GPT teacher head0.277
Teacher spread0.170 · 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