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Record W2938950932 · doi:10.32014/2019.2518-170x.33

CHALLENGING ISSUES OF FRESH WATER WITHIN THE TERRITORY OF EAST KAZAKHSTAN AND ADJACENT AREAS OF CENTRAL KAZAKHSTAN

2019· article· en· W2938950932 on OpenAlexaff
Murat Abikenovich Mukhamedjanov, Jay Sagin, Lyazzat Manatovna Kazanbaeva, Asel Azatkalievna Nurgaziyeva

Bibliographic record

VenueNEWS of National Academy of Sciences of the Republic of Kazakhstan · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil and Environmental Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsScience Citation IndexCitationInclusion (mineral)Index (typography)Library scienceGeographyCentral asiaRegional sciencePolitical scienceEarth sciencePhysical geographyGeologySocial scienceSociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

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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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0080.004
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.030
GPT teacher head0.238
Teacher spread0.208 · 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 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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNEWS of National Academy of Sciences of the Republic of KazakhstanSame topicSoil and Environmental StudiesFrench-language works237,207