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Record W1982261714 · doi:10.5539/mas.v9n4p12

Pollution of the Air Basin in the Cities by Motor Transport and the Industrial Enterprises, Quality Assessment of Atmospheric Air with the Use of Calculation Methods and Instrumental Control

2014· article· en· W1982261714 on OpenAlexvenueno aff
Ilnar Fargatovich Suleimanov, Gennady Vitalievich Mavrin, Damir Afgatovich Kharlyamov, Eduard Belyaev, Aigul Indusovna Mansurova

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Industrial Safety
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceAir pollutionAir quality indexPollutionAtmosphere (unit)STREAMSWork (physics)Quality (philosophy)Atmospheric airEnvironmental engineeringMeteorologyAtmospheric sciencesComputer scienceGeographyEngineering

Abstract

fetched live from OpenAlex

Within this work, field observations of structure and intensity of motor transport streams were conducted, the information about the operating sources of atmosphere pollution from the enterprises in the city of Naberezhnye Chelny, their qualitative and quantitative structure, physical parameters were collected, processed and systematized. On the basis of the obtained data a summary calculation of emissions of the industrial enterprises and motor transport was carried out, the list of the priority polluting substances was defined, the complex index of pollution of the atmosphere was calculated, highways with the greatest transport loading were defined. On the basis of instrumental control the measurements of quality of atmospheric air near highways were carried out, actions for optimization of transport streams and decrease in negative impact were offered.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.258
Teacher spread0.234 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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