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Record W2114009624 · doi:10.1093/humrep/des355

Proposal of guidelines for the appraisal of SEMen QUAlity studies (SEMQUA)

2012· article· en· W2114009624 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

VenueHuman Reproduction · 2012
Typearticle
Languageen
FieldHealth Professions
TopicMale Reproductive Health Studies
Canadian institutionsAchieve Life Sciences (Canada)
Fundersnot available
KeywordsChecklistQuality (philosophy)GuidelineCritical appraisalInclusion (mineral)PsychologyConstructive criticismConstructiveMEDLINEMedical educationCriticismComputer scienceMedicineManagement scienceFamily medicineAlternative medicineProcess (computing)PathologySocial psychologyBiologyEngineeringPolitical science

Abstract

fetched live from OpenAlex

STUDY QUESTION: Is there a need for a specific guide addressing studies of seminal quality? SUMMARY ANSWER: The proposed guidelines for the appraisal of SEMinal QUAlity studies (SEMQUA) reflect the need for improvement in methodology and research on semen quality. WHAT IS KNOWN ALREADY: From an examination of other instruments used to assess the quality of diagnostic studies, there was no guideline on studies of seminal quality. STUDY DESIGN, SIZE AND DURATION: Through systematic bibliographic search, potential items were identified and grouped into four blocks: participants, analytical methods, statistical methods and results. PARTICIPANTS/MATERIALS, SETTING AND METHODS: Our findings were presented to a panel of experts who were asked to identify opportunities for improvement. Then, a checklist was designed containing the questions generated by the items that summarize the essential points that need to be considered for the successful outcome of a SEMQUA. MAIN RESULTS AND THE ROLE OF CHANCE: Eighteen items were identified, from which 19 questions, grouped into four blocks, were generated to constitute the final checklist. An explanation for the inclusion of each item was provided and some examples found in the bibliographic search were cited. LIMITATIONS AND REASONS FOR CAUTION: We consider that not all items are equally applicable to all study designs, and so the hypothetical results are not comparable. For that reason, a score would not be fair to critically appraise a study. This checklist is presented as an instrument for appraising SEMQUAs and therefore remains open to constructive criticism. It will be further developed in the future, in parallel with the continuing evolution of SEMQUAs. WIDER IMPLICATIONS OF THE FINDINGS: The final configuration of the SEMQUA is in the form of a checklist, and includes the items generally considered to be essential for the proper development of a SEMQUA. The final checklist produced has various areas of application; for example, it would be useful for designing and constructing a SEMQUA, for reviewing a paper on the question, for educational purposes or as an instrument for appraising the quality of research articles in this field. STUDY FUNDING/COMPETING INTEREST(S): None.

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)0.011
metaresearch head score (Gemma)0.014
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 score0.244
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.664
GPT teacher head0.664
Teacher spread0.000 · 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