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Record W4200457040 · doi:10.3390/life11121368

The Sixth Edition of the WHO Manual for Human Semen Analysis: A Critical Review and SWOT Analysis

2021· review· en· W4200457040 on OpenAlexaff
Florence Boitrelle, Rupin Shah, Ramadan Saleh, Ralf Henkel, Hussein Kandil, Eric Chung, Paraskevi Vogiatzi, Armand Zini, Mohamed Arafa, Ashok Agarwal

Bibliographic record

VenueLife · 2021
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill University
Fundersnot available
KeywordsSWOT analysisStrengths and weaknessesOperations researchMedicineComputer sciencePsychologyManagementMathematics

Abstract

fetched live from OpenAlex

Semen analysis is the cornerstone of male fertility evaluation with WHO guidelines providing the basis for procedural standardization and reference values worldwide. The first WHO manual was published in 1980, and five editions have been subsequently released over the last four decades. The 6th Edition was published in July 2021. In this review, we identify the key changes of this 6th Edition. Additionally, we evaluate the utility of this 6th Edition in clinical practice using SWOT (strengths, weaknesses, opportunities, and threats) analysis. This new Edition has made the analysis of basic semen parameters more robust, taking into account the criticisms and grey areas of the previous editions. The tests assessing sperm DNA fragmentation and seminal oxidative stress are well-described. The main novelty is that this latest edition abandons the notion of reference thresholds, suggesting instead to replace them with "decision limits". While this seems attractive, no decision limits are proposed for either basic semen parameters, or for extended or advanced parameters. This critical review of the 6th Edition of the WHO laboratory manual combined with a SWOT analysis summarizes the changes and novelties present in this new Edition and provides an in-depth analysis that could help its global use in the coming years.

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)0.017
metaresearch head score (Gemma)0.037
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0100.005
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.009

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 head0.060
GPT teacher head0.400
Teacher spread0.339 · 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
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

Citations249
Published2021
Admission routes1
Has abstractyes

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