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Record W2786834161 · doi:10.5539/sar.v7n2p41

Evaluation of Plant Growth on Expanded Black Cotton Soil

2018· article· en· W2786834161 on OpenAlexvenueno aff
Samwel Nyakach, Seth F.O. Owido, Japheth O. Onyando

Bibliographic record

VenueSustainable Agriculture Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsHuskAerationGreenhouseAgronomyEnvironmental scienceHydroponicsCropNutrientDrainagePlant growthBiologyBotany

Abstract

fetched live from OpenAlex

In aggregate hydroponics, the suitability of a particular medium is often guided by its physical properties. However these may not provide adequate evaluation. By growing a crop, the growth characteristics can also be used to guide medium preparation and selection. Tomatoes (Anna F1 variety) were grown in containers under a greenhouse and provided with equal amount of nutrient solution. The expanded black cotton soil was prepared by mixing with rice husk at a ratio of 90:10, fired at 750oC for 30 minutes and size reduced to various textures. The crops planted in the expanded clay aggregates performed better than the black cotton soil both in terms of stem elongation and enlargement due to improved drainage, nutrient flow and aeration conditions. The root length density was 25654 m m-3 in black cotton soil, being the highest and lowest in the coarse aggregates which had 9433 m m-3.

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)0.006
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.339
Teacher spread0.259 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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