Alexandrovich, K. A. (2023). Taking into Account the Impact of Various Types of Losses When Using Information Modeling Technology in Construction
Why this work is in the frame
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Bibliographic record
Abstract
Objective: The research is devoted to the application and formation of new scientific approaches, the development of practical recommendations, the use of information modeling technology in the activities of the construction complex enterprises at the stages of the life cycle of real estate objects to increase competitiveness and reduce the cost of final products, as well as reduce the timing of projects. Method: Such research methods as theoretical analysis and empirical study, including the main scientific approaches were used: "dialectical," "systemic," "dynamic," "variant," "balance," "modeling." An analysis of the activities of a number of enterprises in the construction industry of the Penza region was carried out. A quantitative assessment of external and internal environment factors affecting the activities of enterprises and their classification was carried out taking into account the influence of each element, and an algorithm of control models was developed using information models in risk conditions, taking into account losses of different levels. Results: During the study, it was established that the formation of losses occurs in conditions of constantly changing factors of the external and internal environment, which require their assessment when determining the main parameters and efficiency of the activities of enterprises of various organizational and economic redistributions of the complex. When moving from stage to stage, loss accumulation and transformation occurs. Conclusions: A flexible management model is proposed that allows you to respond to all changes in the external environment, as well as timely manage costs in the internal environment, including the timing of work, which will allow you to quickly adjust the progress of production processes in space and time when any types of risks occur in the activities of the construction complex enterprises.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it