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Record W1546692 · doi:10.1093/ajcp/97.2.227

让希望之星更亮——祝福非国有科技企业:在企业技术创新与人才发展战略论坛上的讲话

2003· article· en· W1546692 on OpenAlexaboutno aff
杜祥琬

Bibliographic record

Venue企业科协 · 2003
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

We show in this report that fresh frozen plasma (FFP) can be thawed faster using a specifically designed microwave oven (MWO) (WesLabs Plasma Defroster, Westmorland Laboratories, Inc., New Brunswick, Canada) than using 37 degrees C water bath (WB) and that the thawed product was equivalent to FFP thawed by WB. Paired plasma bags (200 mL/bag) from plasma pools were frozen, stored at -35 degrees C, and thawed in parallel, one bag in MWO, the other in WB. Mean thaw time (mean + SD) by MWO was 6.99 + 1.3 minutes; by WB the time was 17.6 + 1.7 minutes (n = 24; P less than 0.005). Rapid calorimetry of thawed plasma showed that MWO-thawed FFP temperature was 20.4 + 2.5 degrees C, whereas WB-thawed FFP was 15.4 + 3.3 degrees C (n = 24; P less than 0.005). Except for thrombin time (MWO = 20.1 seconds; WB = 19.8 seconds; n = 24; P = 0.023), no significant differences were observed in the 23 other coagulation parameters and plasma proteins studied. Faster thawing and freedom from risk of contamination may make MWO the method of choice for emergency thawing of FFP.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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 designNot applicable
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

Citations0
Published2003
Admission routes1
Has abstractyes

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