Effects of <i>Ascophyllum nodosum</i> extract application in the nursery on root growth of containerized white spruce seedlings
Bibliographic record
Abstract
MacDonald, J. E., Hacking, J., Weng, Y. and Norrie, J. 2013. Effects of Ascophyllum nodosum extract application in the nursery on root growth of containerized white spruce seedlings. Can. J. Plant Sci. 93: 735–739. In this preliminary study, Picea glauca seedlings were root drenched with a commercial liquid extract of Ascophyllum nodosum in finisher fertilizer (8N–20P–30K) at the following rates: 1:500, 1:250, 1:125, and 1:75. Fertilizer alone served as control. Applications were made four or eight times over a period of 17 or 43 days, respectively. Compared with control, all rates reduced total root system length in mid October by 44–54%. After freezer storage and then growing under favorable conditions in spring for 21 d, the 1:125 and 1:75 rates increased the number of white roots emerging from the intact peat plug by 42 and 63%, respectively.
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 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 | 0.001 | 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 | 0.000 | 0.001 |
| 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 teacher head, 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".