Bibliographic record
Abstract
Актуальность проблемы грамотного учета затрат в организации объясняется периодическим повышением штрафов за неправильное исчисление налогов и сборов или несвоевременную их уплату. Затраты влияют на определение налогооблагаемой базы по налогу на прибыль организаций, а он является одним из важнейший в РФ и крупных по размеру. Наибольшее количество нарушений, которые регистрирует налоговая службы, касаются именно расчета налога на прибыль организаций и именно в части завышения затрат, и тем самым занижения налогооблагаемой базы. Распределение затрат как по видам продукции, так и по видам самих затрат производится организацией самостоятельно на основе закрепленных способов. Грамотность определения этих способов также является объектом проверки со стороны контролирующих органов. Важно не просто использовать те или иные нормы законодательства, а правильно их интерпретировать. The relevance of the problem of competent cost accounting in the organization is explained by the periodic increase in fines for incorrect calculation of taxes and fees or their late payment. Costs affect the determination of the taxable base for corporate income tax, and it is one of the most important in the Russian Federation and large in size. The largest number of violations registered by the tax authorities relate specifically to thecalculation of corporate income tax and precisely in terms of overestimating costs, and thereby underestimatingthe taxable base. The distribution of costs both by type of product and by type of costs themselves is carried out by the organization independently on the basis of fixed methods. The literacy of the definition of these methods isalso the object of verification by the regulatory authorities. It is important not only to use certain norms of legislation, but to interpret them correctly.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".