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Record W2970773150 · doi:10.3389/fcvm.2019.00138

Advances in Platelet Subpopulation Research

2019· review· en· W2970773150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsPlateletBiologyImmunologyMedicine

Abstract

fetched live from OpenAlex

Although lacking a nucleus, platelets are increasingly recognized not only for their complexity, but also for their diversity. Some 50 years ago platelet subpopulations were characterized by size and density, and these characteristics were thought to reflect platelet aging. Since, our knowledge of platelet heterogeneity has grown to recognize that differences in platelet biochemistry and function exist. This includes the identification of vanguard and follower platelets, platelets with differing procoagulant ability including "COAT-platelets" which enhance procoagulant protein retention on their surface, and most recently, the identification of platelet subpopulations with a differential ability to generate and respond to nitric oxide. Hence, in this mini-review, we summarize the current knowledge of platelet subpopulation diversity focusing on their physical, biochemical, and functional heterogeneity. In addition, we review how platelet subpopulations may change between health and disease and how differences among platelets may influence response to anti-platelet therapy. Finally, we look forward and discuss some of the future directions and challenges for this growing field of platelet research.

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.

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)0.003
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 score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.089
GPT teacher head0.400
Teacher spread0.311 · 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