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A call to standardize the nomenclature of human fetal membrane at the feto-maternal interface

2025· article· en· W4413191876 on OpenAlexfundno aff
Claire E. Kendal‐Wright, John J. Moore, Liping Feng, Ramkumar Menon, Anna L. David, Tina T. Chowdhury, M. Crowther, Connor A. Howe, Nanbert Zhong, Veronica Zaga Clavellina, Pilar Flores‐Espinosa, Nina Truong, Vincent Sapin-Deour, Loı̈c Blanchon, Abir Zahra, Ananth Kumar Kammala, Rahul Cherukuri, Lauren Richardson, Sungjin Kim, Po Yi Lam, Emmanuel Amabebe, Rahul Dev Chauhan, David M. Aronoff, Laura Martin, Jeff Reese, Angela DeTomaso, Suresh K. Bhavnani, Ryan C. V. Lintao, Lourdes Vadillo, Felipe Vadillo‐Ortega, Mariana de Castro Silva, Meredith A. Kelleher, Corinne Belville, Arturo Flores‐Pliego, Sudeshna Tripathy, Shajila Siricilla, Italo Calori, Carlos M. Guardia, Tamás Zakár, Brandie D. Taylor, Bruna Ribeiro de Andrade Ramos, Haruta Mogami, Chan‐Wook Park, Kaitlyn Timmons, Pietro Presicce, Suhas G. Kallapur, Madhuri Tatiparthy, Vikki Abrahamas, Rheanna Urrabaz‐Garza, Michelle M. Coleman, Jessica Selim, Luis Sobrevía, Manuel K. Rausch, Marián Kacerovský, Jossimara Polettini, Sean Murphy, Souvik Paul

Bibliographic record

VenuePlacenta · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Environmental Health SciencesNational Institute of General Medical SciencesSchool of Medicine, Indiana UniversityOregon National Primate Research CenterDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of PittsburghUniversity of California, Los AngelesNational Institutes of HealthUniversidade Federal da Fronteira SulInstituto Nacional de Medicina GenómicaCentre National de la Recherche ScientifiqueYale UniversitySeoul National UniversityVanderbilt University Medical CenterUniversidad Nacional Autónoma de MéxicoNational Institute of Child Health and Human DevelopmentUniversity of Newcastle AustraliaUniversity of the PhilippinesEngineering and Physical Sciences Research CouncilInstitut National de la Santé et de la Recherche MédicaleDavid Geffen School of Medicine, University of California, Los AngelesCase Western Reserve UniversityAurora Research InstituteChaminade University of HonoluluUniversidade Estadual PaulistaChildren’s Hospital of Wisconsin Research InstituteQueen Mary University of LondonHunter New England Local Health DistrictCollege of Medicine, Seoul National UniversityKungliga Tekniska HögskolanUniversidade Nove de JulhoMedical Research CouncilSeattle Children's Research InstituteUniversity of Texas at AustinUniversity of Texas Medical BranchU.S. Food and Drug AdministrationVanderbilt University
KeywordsInterface (matter)NomenclatureFetusObstetricsComputer scienceMedicineBiologyPregnancyGeneticsZoology

Abstract

fetched live from OpenAlex

Despite being one of the largest intrauterine tissues in surface area, the fetal membrane that lines the intrauterine cavity is often overlooked, forgotten, or misidentified in clinical and basic science research. The feto-maternal interface is comprised of the fetal membrane (fetal component) and decidua parietalis (maternal component), which lines the intrauterine cavity and provides essential mechanical, immune, hormonal, and transport support to maintain pregnancy. Fetal membrane plays an important role in triggering and regulating labor via complex signaling cascades. Whilst several researchers have investigated the membranes world-wide, nomenclature remains inconsistent, leading to widespread ambiguity across inter-disciplinary disciplines involving science, bioengineering, and reproductive medicine. The ongoing confusion regarding its terminology, origins, structure, and function has resulted in several significant issues, including diagnostic errors and misrepresentation clinically, limitations and inaccuracies in scientific research, and regulatory and clinical miscommunication. Therefore, the Fetal Membrane Society (FMS) calls upon the field to standardize fetal membrane nomenclature, define its architecture, and summarize its region-specific differences to facilitate understanding of its biological role. Clear and consistent identification of the fetal membrane is essential in improving research accuracy, clinical outcomes, and effective communication within and between the medical and scientific communities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.302
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations3
Published2025
Admission routes1
Has abstractyes

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