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Supplementary material from "Allometric scaling relationships in mouse placenta"

2022· other· en· W6939934107 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsConceptusScalingPlacentaFetusOffspringUmbilical arteryEndocardiumEmbryogenesisUterine artery

Abstract

fetched live from OpenAlex

Fetal growth and maturation are highly intertwined with placental development during pregnancy. Here we used placental vascular morphology measurements (depth and span) as well as the umbilical artery (UA) diameter of previously published studies on three different mouse strains (C57BL6/J, CD-1 and BALB/c), which were exposed to different conditions (combination Antiretroviral Therapy—cART, chronic maternal hypoxia and malaria infection) at different embryonic days, to test the hypothesis that placental vascularization and specifically the UA size, affect conceptus weight. Interaction of each study parameter with embryonic day, strain and exposure to treatments are studied to investigate the stability of the scaling relationships across and/or within strains and conditions. In addition, the effect of UA artery diameter on the placental growth measurements (depth and span) is studied. These results show that the power-law scaling relationship of conceptus weight and placental depth with the UA diameter is conserved across strains and conditions with the scaling exponent of approximately 3/8 and 5/8, respectively. By contrast, the relationship between conceptus weight and either the placental span or depth is different between strains and conditions, suggesting multiple mechanisms of vascular adaptation.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.517
Threshold uncertainty score0.689

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5170.136

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 head0.038
GPT teacher head0.223
Teacher spread0.185 · 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.

Study designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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