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Record W4234857896 · doi:10.1097/ta.0b013e31821a4d89

PlasmaLyte

2011· article· en· W4234857896 on OpenAlexaff
Sandro Rizoli

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2011
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsHypovolemiaMedicineShock (circulatory)AcidosisAnesthesiaMetabolic acidosisCardiologyInternal medicine

Abstract

fetched live from OpenAlex

PlasmaLyte is a family of balanced crystalloid solutions with multiple different formulations available worldwide according to regional clinical practices and preferences. It closely mimics human plasma in its content of electrolytes, osmolality, and pH. These solutions also have additional buffer capacity and contain anions such as acetate, gluconate, and even lactate that are converted to bicarbonate, CO2, and water. The advantages of PlasmaLyte include volume and electrolyte deficit correction while addressing acidosis. It shares the same problems as most other crystalloid fluids (fluid overload, edema with weight gain, lung edema, and worsening of the intracranial pressure). A unique concern is that most formulations contain magnesium, which may affect peripheral vascular resistance, heart rate, and worsen organ ischemia. There are few studies on its use in trauma or hypovolemic shock. There is no evidence that PlasmaLyte is superior to other crystalloids for the prehospital management of traumatic hypovolemia.

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 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.014

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 head0.044
GPT teacher head0.321
Teacher spread0.277 · 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 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

Citations32
Published2011
Admission routes1
Has abstractyes

Explore more

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