MétaCan
Menu
Back to cohort
Record W7115705036 · doi:10.5281/zenodo.17956680

YURAK YETISHMOVCHILIGINI KOMPLEKS DAVOLASHDA XALQ TABOBATI USULLARINING KLINIK SAMARADORLIGINI BAHOLASH

2025· article· uz· W7115705036 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageuz
FieldSocial Sciences
TopicEducation, Innovation and Language Studies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsOverprintingOpting outOrcein

Abstract

fetched live from OpenAlex

“Yurak yetishmovchiligi­ni kompleks davolashda xalq tabobati usullarining klinik samaradorligini baholash” mavzusida olib borilgan ushbu ishda an’anaviy davolash usullariga qo‘shimcha ravishda qo‘llaniladigan xalq tabobati vositalarining (dori o‘simliklari, fitoterapiya, tabiiy biostimulyatorlar) yurak etishmovchiligi belgilari, bemorlarning umumiy holati va laborator-instrumental ko‘rsatkichlarga ta’siri o‘rganilgan. Tadqiqot natijalari xalq tabobati usullari kompleks terapiya tarkibida qo‘llanganda yurak qisqarish funksiyasini yaxshilashi, simptomlarni kamaytirishi va bemorlarning hayot sifatini oshirishini ko‘rsatdi.

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)0.003
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0740.026

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 head0.043
GPT teacher head0.329
Teacher spread0.286 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicEducation, Innovation and Language StudiesFrench-language works237,207