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Record W1988004632 · doi:10.1111/vox.12184

Aggregates in platelet concentrates

2014· article· en· W1988004632 on OpenAlexaff
Pieter F. van der Meer, Larry J. Dumont, Miquel Lozano, N. Bondar, J.Shuk-Yee Wong, Sue Ismay, Joanne Pink, Walter Nußbaumer, J. Coene, Hendrik B. Feys, Veerle Compernolle, Dana V. Devine, David Howe, Che Kit Lin, Jenny Sun, Juergen Ringwald, Erwin Strasser, Reinhold Eckstein, Axel Seltsam, Paolo Perseghin, Patrizia Proserpio, Shinobu Wakamoto, Mitsuaki Akino, Shigeru Takamoto, Kenji Tadokoro, Diana Teo, Pei Huey Shu, Sze Sze Chua, Teresa Jimenéz‐Marco, Joan Cid, Emma Castro, Irene Muñoz, H. Gulliksson, Per Sandgren, Stephen Thomas, Juraj Petrík, Kevin McColl, Hany Kamel, James Dugger, Joseph D. Sweeney, Jed B. Gorlin, Laurie J. Sutor, Doug Heath, Merlyn Sayers

Bibliographic record

VenueVox Sanguinis · 2014
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsCanadian Blood Services
Fundersnot available
KeywordsClassicsLibrary scienceArtArt historyPhilosophyComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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 designBench or experimental
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

Citations24
Published2014
Admission routes1
Has abstractno

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