Bibliographic record
Abstract
Twenty two substrates were developed and tested for two different green roof plant production methodologies. Growth rate analysis of Sedum sp. revealed distinct differences in performance of the mat substrates across a two year time frame with substrate water holding capacity (v/v) being a primary promoter of rapid mat coverage. Tray substrate analysis revealed numerous component options provided similar production speeds, with diverse and beneficial physical properties being described. Zebra and Quagga mussel shells proved to be a sustainable and beneficial component option for both mat and tray substrates. Further substrate component identification resulted in Biochar being investigated for its potential use in green roof media mixtures. The additions of incremental amounts of biochar into control substrates reduced bulk density by up to 20%, while simultaneously increasing volumetric water holding capacity to 54%, 12% greater than that of the control. Sedum plant growth in biochar revealed the lowest shoot dry weights resulting from no biochar additions. Substrate and plant water relationships were explored further with four substrates being planted with four diverse herbaceous and succulent plant communities. Substrate composition and plant community was observed to significantly affect dry down rates.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".