Bibliographic record
Abstract
Here we describe the standardised protocol used by the Canadian Airborne Biodiversity Observatory (CABO) to measure leaf water content and specific leaf area, using the WinFOLIA™ software (Régent Instruments). These leaf area and water measurements are done on a subset of leaves from the same bulk leaf sample used to measure leaf spectral reflectance and transmittance. Briefly, after removing their petioles, fresh leaves are weighed, rehydrated for 6 h, scanned for total leaf area and weighed again; they are then oven-dried at 65 ºC for 72 h, and weighed one last time. This allows us to measure leaf dry matter content and its complement, leaf water content, as well as leaf relative water content. Leaf area measurements are used to estimate specific leaf area, a key functional trait central to the leaf economics spectrum. Specific leaf area allows us to estimate equivalent water thickness and to convert concentrations of foliar biochemical constitutents from a leaf mass to a leaf area basis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.013 |
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".