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Record W4285260609 · doi:10.37590/able.v42.art59

Do It Yourself (DIY) Seed Kits to Evaluate the Effects of Fertilizer on Plant Growth Rates

2022· article· en· W4285260609 on OpenAlexaff
Charlotte De Araujo, Patricia A. Wright

Bibliographic record

VenueAdvances in Biology Laboratory Education · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of Guelph
FundersDirectorate for Biological Sciences
KeywordsFertilizerPlant growthAgronomyHorticultureEnvironmental scienceBiologyMathematics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.308
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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