MétaCan
Menu
Back to cohort
Record W2197831191 · doi:10.1093/humrep/dev305

‘How to count sperm properly’: checklist for acceptability of studies based on human semen analysis

2015· article· en· W2197831191 on OpenAlexaff
Lars Björndahl, Christopher L. R. Barratt, David Mortimer, Pierre Jouannet

Bibliographic record

VenueHuman Reproduction · 2015
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsAchieve Life Sciences (Canada)
Fundersnot available
KeywordsSemenChecklistSemen analysisSpermAndrologyGynecologyMedicineBiologyInfertilityPregnancyGenetics

Abstract

fetched live from OpenAlex

STUDY QUESTION: Can a tool be developed for authors, reviewers and editors of the ESHRE Journals to improve the quality of published studies which rely on semen analysis data? SUMMARY ANSWER: A basic checklist for authors, reviewers and editors has been developed and is presented. WHAT IS KNOWN ALREADY: Laboratory work which includes semen analysis is burdened by a lack of standardization. This has significant negative effects on the quality of scientific and epidemiological studies, potential misclassification of patients and the potential to impair clinical treatments/diagnoses that rely on accurate semen quality information. Robust methods are available to reduce laboratory error in semen analysis, inducing adherence to World Health Organization techniques, participation in an external quality control scheme and appropriate training of laboratory personnel. However, journals have not had appropriate systems to assess if these methods have been used. STUDY DESIGN, SIZE, DURATION: After discussion at a series of Associate Editor Meetings of the ESHRE Journals the authors of the present text were asked to propose a tool for authors, reviewers and editors of the ESHRE Journals to ensure a high quality assessment of submitted manuscripts which rely on semen analysis data, including a detailed verification of the relevance and the quality of the methods used. PARTICIPANTS/MATERIALS, SETTING, METHODS: N/A. MAIN RESULTS AND THE ROLE OF CHANCE: A basic checklist for authors, reviewers and editors is presented. The checklist contains key points which should be considered by authors when designing studies and which provides essential information for when the submitted manuscript is evaluated. For published articles the answers in the checklist are suitable to be available as supplementary data, which will also reduce the space necessary for technical details in the printed article. LIMITATIONS, REASONS FOR CAUTION: Guidelines such as these should not be used uncritically. It is therefore important that submitting authors, in situations where their study does not comply with the basic requirements for semen analysis, not only explain all methodological deviations but also declare the level of uncertainty in their analyses and how it complies with, or might confound, the aims of the study. WIDER IMPLICATIONS OF THE FINDINGS: The fundamental importance of appropriate and robust methodology to facilitate advances in scientific understanding and patient management and treatment, is now accepted as being paramount. Use of the semen analysis checklist should be part of this process, and when completed and signed by the corresponding author at the time of submitting a manuscript should result in greater transparency, and ultimately uniformity. It is hoped that this initiative will pave the way for wider adoption of the methodology/reporting by other biomedical, epidemiological and scientific journals, and ultimately become the standard of practice for papers reporting semen analysis results obtained in laboratory and clinical andrology. Systems to assist referees, authors and editors to present high quality findings should have a significant impact on the field of reproductive medicine. STUDY FUNDING/COMPETING INTERESTS: No funding was obtained for this work. The authors have no competing interests in relation to the present publication and checklist. TRIAL REGISTRATION NUMBER: N/A.

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)0.316
metaresearch head score (Gemma)0.586
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3160.586
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0080.010
Bibliometrics0.0120.006
Science and technology studies0.0040.006
Scholarly communication0.0080.014
Open science0.0090.008
Research integrity0.0140.009
Insufficient payload (model declined to judge)0.0240.015

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 head0.146
GPT teacher head0.381
Teacher spread0.235 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainReporting
GenreMethods

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

Citations177
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueHuman ReproductionSame topicSperm and Testicular FunctionFrench-language works237,207