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Record W2419003339 · doi:10.1097/grf.0000000000000149

Minimally Invasive Hysterectomy

2015· review· en· W2419003339 on OpenAlexaff
Beri Ridgeway, Megan Buechel, Benjamin Nutter, Tommaso Falcone

Bibliographic record

VenueClinical Obstetrics & Gynecology · 2015
Typereview
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicineLaparoscopyHysterectomyRandomized controlled trialLaparoscopic hysterectomyMinimally invasive proceduresSurgeryMeta-analysisGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

To compare conventional minimally invasive (MIS) approaches and newer technology approaches in women undergoing hysterectomy for benign disease. PubMed was searched for all pertinent randomized-controlled trials (RCTs). Selected outcomes were compared using standard meta-analysis methods. Three RCTs compared conventional MIS to robotic-assisted hysterectomy and 5 RCTs compared conventional laparoscopy to single-incision hysterectomy. There were no significant differences in outcomes. A subanalysis comparing conventional to robotic-assisted laparoscopy found an association between conventional laparoscopy and shorter operative time. Newer technology approaches do not confer an advantage over conventional MIS approaches in women undergoing hysterectomy for benign disease.

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)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.004

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 head0.198
GPT teacher head0.454
Teacher spread0.256 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2015
Admission routes1
Has abstractyes

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