MétaCan
Menu
Back to cohort
Record W1487926964 · doi:10.1002/dvdy.24134

Developmental origins and functions of stromal cells in the normal and diseased mammalian kidney

2014· article· en· W1487926964 on OpenAlexafffund
Winny Li, Sunny Hartwig, Norman D. Rosenblum

Bibliographic record

VenueDevelopmental Dynamics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversity of Prince Edward IslandHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsBiologyMesenchymeStromal cellKidney developmentKidneyPopulationMesenchymal stem cellOrganogenesisUreteric budCell biologyEndocrinologyGeneticsCancer researchEmbryonic stem cellMedicineGene

Abstract

fetched live from OpenAlex

The kidney is a model developmental paradigm of vertebrate organogenesis. As in many other organs, kidney development involves reciprocal inductive tissue interactions between multiple cell lineages. The most well defined of these interactions occurs between the ureteric bud and the nephrogenic mesenchyme. A population of mesenchymal cells distinct from nephrogenic precursors and termed stromal cells, have been relatively understudied. Yet existing knowledge indicates that stromal cells are critical regulators in the normal and diseased kidney. This commentary reviews current knowledge regarding the origin and functional roles of the stromal cell population during kidney development. Gaps in our current understanding of renal stromal cells and future directions needed to advance this expanding field of study are highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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 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

Citations66
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueDevelopmental DynamicsSame topicRenal and related cancersFrench-language works237,207