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Record W6948617684 · doi:10.5281/zenodo.11362948

Parasportchilarni kunlik harakat kinematikasini tahlil qilish orqali sport natijalarini yaxshilash

2024· article· uz· W6948617684 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageuz
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsIndustry, Tourism and Investment
Fundersnot available
KeywordsWork (physics)Government (linguistics)Perspective (graphical)Product (mathematics)Focus (optics)

Abstract

fetched live from OpenAlex

Mazkur ilmiy tadqiqot ishida natijalarning amaliy ahamiyati, para sportning bilan bilan shug‘ullanuvchi sportchilarning kunlik harakatlarining kinematikasini tahlil qilish orqali hozirgi jismoniy holatlari hamda jismoniy imkoniyatlari yaxshilash. Musobaqalarga tayyorgarlik bosqichida sportchilarning mushaklar guruhlaridagi o‘zgarishlar o‘rganilib, mushak guruhlari holatiga mos mashqlar majmuasi berilib, ulardagi o‘zgarishlar tahlil qilingan.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0040.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1300.073

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 head0.036
GPT teacher head0.235
Teacher spread0.199 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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