Forms and rates of economic and physical depreciation by type of assets in Canadian industries
Bibliographic record
Abstract
This paper introduces a method for performing large-scale studies of forms and rates of economic and physical depreciation by type of assets in Canadian industries. A fractional function representation for the form of economic depreciation is introduced where the numerator represents the form of economic depreciation without adjustment, and the denominator represents the form of either the gross or the net physical depreciation. This representation provides a clear picture of the relationship in both form and rate between economic and physical depreciation. The forms of economic and physical depreciation (except the gross physical depreciation) are all convex, while the exceptional one is concave. This is one of the research papers studied at Statistics Canada in the evolving search for a better methodology for estimating depreciation patterns. Based on the findings of this paper, with more survey data available, and following a more conventional approach, a project is currently underway at Statistics Canada. Gross physical depreciation will be considered as one of the adjustment factors for the price-age-date profile.
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".