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Record W2561961427 · doi:10.1155/2016/4860284

Quality Assessment of Established and Emerging Blood Components for Transfusion

2016· review· en· W2561961427 on OpenAlexafffund
Jason P. Acker, Denese C. Marks, William P. Sheffield

Bibliographic record

VenueJournal of Blood Transfusion · 2016
Typereview
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsMcMaster UniversityCanadian Blood ServicesUniversity of Alberta
FundersCanadian Blood Services
KeywordsApheresisWhole bloodBlood componentBlood productMedicineIntensive care medicineBlood transfusionThrivingBlood donorPlateletRed blood cellBlood donationsSurgeryImmunologyPsychology

Abstract

fetched live from OpenAlex

Blood is donated either as whole blood, with subsequent component processing, or through the use of apheresis devices that extract one or more components and return the rest of the donation to the donor. Blood component therapy supplanted whole blood transfusion in industrialized countries in the middle of the twentieth century and remains the standard of care for the majority of patients receiving a transfusion. Traditionally, blood has been processed into three main blood products: red blood cell concentrates; platelet concentrates; and transfusable plasma. Ensuring that these products are of high quality and that they deliver their intended benefits to patients throughout their shelf-life is a complex task. Further complexity has been added with the development of products stored under nonstandard conditions or subjected to additional manufacturing steps (e.g., cryopreserved platelets, irradiated red cells, and lyophilized plasma). Here we review established and emerging methodologies for assessing blood product quality and address controversies and uncertainties in this thriving and active field of investigation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.383
Teacher spread0.318 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations77
Published2016
Admission routes2
Has abstractyes

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