MétaCan
Menu
Back to cohort
Record W11082349

Особенности обоснования технических средств для противоэрозионной обработки почв

2012· article· en· W11082349 on OpenAlexaboutno aff
Пазова Таймира Хасановна, Балкаров Руслан Асланбиевич, Сохроков Анатолий Хазритович, Дохов Магомед Пашевич, Хамоков Хажсет Аскерханович, Твердохлебов Сергей Анатольевич

Bibliographic record

VenueПолитематический сетевой электронный научный журнал Кубанского государственного аграрного университета · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLand Use and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)ErosionAgricultureAgricultural engineeringEnvironmental resource managementWater resource managementGeographyEnvironmental scienceComputer scienceEngineeringGeologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

In the article, main principles and methodical bases of the complex analysis of actions for research of influence of influences on soil subject to erosion are stated at cultivation of agricultural crops for the purpose of preservation and increase of its fertility

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.038
GPT teacher head0.352
Teacher spread0.314 · 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
GenreMethods

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueПолитематический сетевой электронный научный журнал Кубанского государственного аграрного университетаSame topicLand Use and ManagementFrench-language works237,207