Bibliographic record
Abstract
Nine stream channel characteristics (channel unit frequency, channel unit length, pool spacing, depth variability, width variability, large woody debris jam spacing, large woody debris volume, relative roughness, and average bank‐full width used as a scale) were measured in 12 reaches in old growth forests on Haida Gwaii and Vancouver Island. They are applied to calculate a Euclidean distance measure of dissimilarity between all possible reach pair combinations. Frequency distributions of the resulting dissimilarity values express the range of variability present in the streams analyzed and enable definition of ranges of favorable and unfavorable comparisons. Reach pairs exhibiting high dissimilarity values have significant differences in several key stream channel characteristics that vary between reach pairs. Those reaches consistently appearing in reach pairs with high dissimilarity values exhibit significant variance from the norm for the group. Dissimilarity distributions provide a basis for appraising the outcome of stream channel manipulation (for example, in channel “restoration” programs) and for selecting channel pairs that are sufficiently similar to act as treatment and control units in experimental manipulations.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".