Base–age Invariant Polymorphic Height Growth and Site Index Equations for Peatland Black Spruce Stands
Bibliographic record
Abstract
Abstract The goal of this study was to develop base–age invariant polymorphic height growth and site index equations for peatland black spruce (Picea mariana [Mill.]; BSP) stands situated within the western portion of the Northern Clay section of the Canadian Boreal Forest region. Procedurally, equation parameters were estimated via ordinary least squares analysis using 291 mean dominant height − mean stand age (Hd − As) data pairs derived from 42 permanent sample plots (PSPs). The predictive ability of the resultant height growth equation was evaluated by examining mean absolute and relative errors and associated 95% prediction intervals over 5-, 15-, 25-, 35-, and 45-year projection periods. Furthermore, using an independent data set consisting of 129 Hd − As data pairs derived from 24 PSP, the new height growth equation was compared with two preexisting equations. Overall, the results indicated that the predictions derived from the new equation were unbiased irrespective of error type or projection period length and that the new equation exhibited greater predictive accuracy and was more consistent with expected dominant height development patterns than the preexisting equations. Consequently, the new equations are recommended for use when describing height growth patterns or quantifying site quality within peatland black spruce stands.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".