Identification of Constraining Experimental-Design Factors in Mycorrhizal Pot-Growth Studies
Bibliographic record
Abstract
In the objective of testing the design of pot-growth experiments, we conducted two greenhouse studies of a “dwarf” sunflower cultivar and an arbuscular mycorrhizal (AM) fungus to determine how pot size and inoculum distribution affect plant growth and AM symbiosis. As predicted, large-potted plants developed a greater overall biomass and root colonization than small-potted ones which we attributed to the larger “rootable” volume. Furthermore, plants grown in a band of high density inoculum substrate showed a higher prevalence of fungal vesicles (sites of lipid storage) indicating a more advanced level of root colonization compared to those grown in a dispersed inoculum substrate; this likely being due to the higher frequency of interaction between roots and fungal propagules. In a second experiment, large-potted AM plants showed a greater tolerance to water deficit than non-AM control plants; however, this mycorrhizal effect was not detected among small-potted plants. We conclude that careful consideration should be made toward design parameters to limit result biases and ultimately facilitate comparison of findings between studies.
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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 | 0.037 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".