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Record W3001896555 · doi:10.1101/2020.01.15.20017657

Therapeutic use of blood products for the treatment of autoimmune hemolytic anemia: A network meta-analysis protocol

2020· preprint· en· W3001896555 on OpenAlexaff
Jiawen Deng

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHematocritAutoimmune hemolytic anemiaAnemiaMedicineHemoglobinRed blood cellAdverse effectReticulocyteMeta-analysisBlood transfusionHemolytic anemiaHypoxia (environmental)HemolysisImmunologyBilirubinInternal medicineOxygenBiologyChemistry

Abstract

fetched live from OpenAlex

ABSTRACT Autoimmune hemolytic anemia is a rare blood disorder that can result in anemic hypoxia. Currently, red blood cell (RBC) transfusion is the only effective method of treating this condition. We propose a network meta-analysis that investigates whether the use of different types of blood products (e.g. suspended RBC, leukoreduced RBC, washed RBC, etc.) can decrease adverse events, increase the rate of remission and improve lab results, including hemoglobin, RBC, reticulocyte counts, hematocrit and total bilirubin.

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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.579
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
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 head0.185
GPT teacher head0.343
Teacher spread0.158 · 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 designMeta-analysis
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

Citations1
Published2020
Admission routes1
Has abstractyes

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