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Record W2151293318 · doi:10.7322/jhgd.19984

[no title]

2010· article· W2151293318 on OpenAlexaff
Igor Ivanecky, Jaques Belik

Bibliographic record

VenueJournal of Human Growth and Development · 2010
Typearticle
Language
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

OBJETIVO: o acúmulo de líquido peritoneal é um achado comum em muitas crianças com distúrbios abdominais e sua geração é secundária ao aumento da permeabilidade vascular. A contribuição da circulação arterial versus venosa para a formação de edema e acúmulo de líquido peritoneal é mal compreendida. Estudos realizados in vivo mais de duas décadas atrás, sugeriram que a vênulas são mais importantes que os vasos arteriais no processo de formação de edema. O objetivo deste trabalho é analisar os efeitos das mudanças na pressão intravascular e a inflamação mediada pela bradicinina na permeabilidade venosa e vascular mesentérica de ratos. MÉTODO: artérias mesentéricas (MA) e veias (MV) foram montadas em cânulas de vidro, por via intravenosa preenchida com dextran fluorescentes e incremental pressurizado acima de seus valores fisiológicos in vivo. Permeabilidade vascular para dextrana foi determinada a 100, 200 e 300% de pressões fisiológicas. RESULTADOS: a permeabilidade vascular estava presente em todas as medidas para ambos os vasos e sua magnitude diretamente proporcional à pressão intravascular. A bradicinina (10-5 M) aumentou significativamente a permeabilidade da MV, mas não no MA. CONCLUSÃO: o acúmulo de líquido abdominal relacionado à doença inflamatória intestinal é mais provável de ser secundária a venosa, em oposição à fuga vascular arterial.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.966
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0340.012

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 head0.013
GPT teacher head0.256
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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