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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.114

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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