Do It Yourself (DIY) Seed Kits to Evaluate the Effects of Fertilizer on Plant Growth Rates
Bibliographic record
Abstract
With the increasing world population, it is critical to develop sustainable strategies for food production.This remote first year laboratory exercise for non-biology students provided a handson approach to small scale plant production.Students created indoor mini-gardens by independently planting either beans or corn seeds under varying conditions to evaluate the claim, "Corn and beans are easy to grow and fertilizer has little effect on growth."To carry out their experiments, students received take-home seed kits containing either bean or corn seeds, peat pellets, and fertilizer, accompanied with detailed experimental procedures.Over the semester, students monitored plant growth in the presence or absence of fertilizer, documenting both qualitative and quantitative results, such as size, length and number of leaves.To promote collaboration in an online setting, students were encouraged to compare their results using discussion boards.Overall the majority (87%, n=47) of students felt this laboratory exercise developed a strong appreciation of plants and were motivated (89%, n=47) to continue with their indoor garden.Firstpage
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.016 |
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".