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Record W4322708492 · doi:10.1051/e3sconf/202337105024

Economic features of services and energy cost for engineering systems

2023· article· en· W4322708492 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

VenueE3S Web of Conferences · 2023
Typearticle
Languageen
FieldEngineering
TopicConstruction Management and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessUnit (ring theory)Service (business)ElectricityQuarter (Canadian coin)Unit costWater supplyEnvironmental economicsPayback periodOperations managementEngineeringEconomicsEnvironmental engineeringProduction (economics)Marketing

Abstract

fetched live from OpenAlex

There are the results of some municipal services actual specific cost for residential apartment building. These services consist of cold water supply system; drainage and sewage systems; electricity; collection and disposal of municipal solid waste system. Authors did not indicate the specific operating cost for hot water supply and heating systems because their cost was constant. Research period: from 1st quarter of 2018 year to the 2nd quarter of 2022 year. This period was acute phase of Covid-19 pandemic period. Authors have written the dynamics changes in the cost of considered services. Researchers have presented additional factors which affect to the unit cost of municipal services in this paper. There is a brief overview of management companies types which could be in municipal service system. Also it has been considered their capabilities and limitations in creating tariffs process. Authors have identified different trends in the engineering service unit cost changing process. This article could be interested for management companies and tariffs planning departments of public municipal service system in different parts of Russian Federation. Results which were presented in this paper could be used in predictive mathematical models of municipal services economical parts in critical as pandemic or other emergency situations.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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