Temporal development of decaying log habitats in wet sprucefir stands in east-central British Columbia
Bibliographic record
Abstract
Time since death and time since fall were estimated for hybrid spruce (Picea glauca (Moench) Voss × Picea engelmannii Parry ex Engelm.) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) logs to quantify temporal changes in log decay and habitat quality in east-central British Columbia. We sampled 136 logs (72 spruce and 64 fir) for species, size, and morphological attributes and used dendroecological techniques to estimate year of death (n = 97) and fall (n = 22). Time since death and time since fall of spruce and fir were similar in decay classes 1 and 2; fir was older than spruce in more advanced stages of decay. Discriminant analysis based on time since fall correctly classified logs into four decay classes for 67% and 80% of spruce and fir, respectively. Function as wildlife habitat changed significantly as logs decayed. Logs served as elevated runways for approximately 15 years and then increased in value as habitat for invertebrates and insectivores as wood softened and vegetation established. Concealed spaces increased as the wood decomposed but decreased when logs collapsed. We conclude that decay classes represent biologically and statistically significant stages of log decomposition that are relevant to wildlife habitat and therefore provide a useful construct for model development and field interpretation..
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".