Определение величины лизинговых платежей с учетом действия инфляции: аннотация к дипломной работе / Виктория Геннадьевна Бороховская; БГУ, Факультет прикладной математики и информатики, Кафедра математического моделирования и анализа данных; науч. рук. Кирлица В. П.
Bibliographic record
Abstract
The object of research: lease payments flows.Objective: determining the value of the lease payments, taking into account the action of inflation, using the adjustment lease payments.Methods: adaptive approach algorithms: the annual, semi-annual, quarter payments adjustment, the use of inflation for the previous years, the probability distribution.Results: conclusions about the actual lease payments, which are more adapted to real situations; different conclusions about the probability distribution of the residual value.Scope: Minimization of risk premiums, the possibility of payments to be more flexible and take into account the interests of both parties.
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 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) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.010 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.043 | 0.014 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".