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Record W2797546859 · doi:10.17116/jnevro20181181245-51

Alcohol withdrawal syndrome dynamics during treatment with nooclerin (deanoli aceglumas)

2018· article· en· W2797546859 on OpenAlexaff
Т. В. Агибалова, Oleg Zh. Buzik, O.V. Rychkova, A.V. Smyshlyaev, В. В. Румбешт

Bibliographic record

VenueS S Korsakov Journal of Neurology and Psychiatry · 2018
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsBritish Columbia Centre on Substance Use
Fundersnot available
KeywordsAlcohol withdrawal syndromeMedicineAlcoholAdverse effectRandomized controlled trialAnesthesiaClinical trialWithdrawal syndromeInternal medicine

Abstract

fetched live from OpenAlex

AIM: To study the efficacy of nooclerin (deanoli aceglumas) in alcohol withdrawal syndrome assessed by clinical and biochemical characteristics. MATERIAL AND METHODS: A multicenter, open, randomized, comparative study of nooclerin in the complex treatment of alcohol withdrawal syndrome included 90 patients. The patients were randomized into nooclerin group (n=55) and control group (n=35). RESULTS AND CONCLUSION: Nooclerin reduced alcohol withdrawal symptoms more significantly throughout the whole study period. There were significant between-group differences on the Clinical Institute Withdrawal Assessment of Alcohol Scale (CIWA-Ar) and the Multidimensional Fatigue Inventory (МFI-20). However, patients exhibited no excessive activity. No adverse side-effects were observed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.658

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)0.0000.000

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 head0.008
GPT teacher head0.252
Teacher spread0.243 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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