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Record W2735717190 · doi:10.19070/2379-156x-170002e

Synthetic Vasopressin and Oxytocin Analogs and Their Potential Use in Hemorrhagic, Traumatic and Septic Shock: A Personal Perspective

2017· article· en· W2735717190 on OpenAlexfundno aff
Altura Bm, Altura Bt, A Carella

Bibliographic record

VenueInternational Journal of Surgery and Research · 2017
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsnot available
FundersAlbert Einstein College of Medicine, Yeshiva UniversitySchool of Medicine, New York UniversityYork UniversityYeshiva University
KeywordsVasopressinSeptic shockOxytocinPerspective (graphical)Hemorrhagic shockShock (circulatory)Traumatic ShockPsychologyMedicineIntensive care medicineAnesthesiaNeuroscienceInternal medicineSepsisComputer science

Abstract

fetched live from OpenAlex

As one of us has stated many years ago, “shock is a significant and sustained loss of effective circulating blood volume. It will eventuate in hypoperfusion of critical peripheral tissues, thus leading to a deficit in transcapillary exchange function in critical organ regions. Clinically, there are five major types of circulatory shock: cardiogenic; septic; distributive; anaphylactic; and hypovolemic. Hypovolemic shock (HS) is, primarily, due to a marked decrease in venous return, falling arterial blood pressure, and ventricular preload, and usually is caused by hemorrhage, dehydration, excessive diarrhea, trauma, excessive fluid loss from severe burns, increased positive intrathoracic pressure, excessive urinary fluid loss resulting from diuretics, side effects of many chemotherapeutic agents and radiation in cancer patients, or depressed vasomotor tone in the microcirculation

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.174
GPT teacher head0.439
Teacher spread0.265 · 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
GenreCommentary

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

Citations2
Published2017
Admission routes1
Has abstractyes

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