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Record W2939000583 · doi:10.1201/9780429457166

Reconstructive and Reproductive Surgery in Gynecology, Second Edition

2018· book· en· W2939000583 on OpenAlexaff
Malcolm G. Munro, Victor Gomel

Bibliographic record

Venuenot available
Typebook
Languageen
FieldMedicine
TopicGynecological conditions and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineReconstructive surgeryGeneral surgeryGynecologySurgery

Abstract

fetched live from OpenAlex

This new edition of a groundbreaking book is now in two volumes, on 'Fundamentals, Symptoms, and Conditions‘ on 'Reconstructive and Fertility Preserving Surgery and Procedures. From a distinguished editorial team and internationally recognized contributors the text educates surgeons on the techniques and procedures now needed in gynecology, with a special focus on reconstructive vaginal, hysteroscopic, laparoscopic, and laparotomic surgery, including that designed to preserve or enhance fertility. The reader can now more readily understand pathogenesis, appropriate investigation, and application of both surgical and nonsurgical strategies and techniques. The two volumes contain over 20 new chapters and in the integral ebook, over 140 instructional videos; each chapter has Key Points summarized.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.101
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1010.047

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 head0.024
GPT teacher head0.264
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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