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Record W3153893582 · doi:10.28983/asj.y2021i3pp94-98

Ensuring the safety of the functioning of mobile means of mechanization of vehicles and technological processes of AIC

2021· article· en· W3153893582 on OpenAlexaboutno aff
Роман Владимирович Шкрабак

Bibliographic record

VenueThe Agrarian Scientific Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicTransportation Systems and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsMechanizationAgricultureVariety (cybernetics)Work (physics)Production (economics)Agricultural machineryBusinessQuarter (Canadian coin)Transport engineeringAgricultural engineeringOperations managementAgricultural economicsForensic engineeringNatural resource economicsEngineeringGeographyComputer scienceEconomics

Abstract

fetched live from OpenAlex

Agricultural production is distinguished by a variety of activities carried out at all seasons of the year and in almost all soil and climatic zones, producing food products and raw materials. Almost a quarter of the volume of work in various zones of the country falls on transport and technological processes. The latter are characterized by road traffic accidents. Determining among them are vehicle collisions, which are accompanied by severe consequences every year. In 2018 alone, 71167 cases of road accidents due to collisions killed 7671 people and injured 109,717. Authors offered a well-grounded and developed strategy and tactics for the dynamic reduction and elimination of occupational injuries and diseases of people.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.012
GPT teacher head0.187
Teacher spread0.175 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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