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Record W4393243635 · doi:10.53555/sfs.v8i3.2378

Hydroponics: An Overview Of Advanced Growing Approaches

2022· article· en· W4393243635 on OpenAlexvenueno aff
Jayanti Ballabh, Mansi Nautiyal, Raja Joshi, Mahipal Singh, Guarav Jain, Neha Saini

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
Fundersnot available
KeywordsHydroponicsComputer scienceBiology

Abstract

fetched live from OpenAlex

Many man-made factors, like industrialization and urbanisation, have made soil-based farming more challenging. Soil fertility and quality are also diminished by unchecked chemical usage in agriculture, climate change, and abrupt events in nature. Because of this need, researchers have come up with a new method of growing plants: hydroponics, which does not use soil. Growing plants in a nutrient-rich water solution is called hydroponics. Hydroponics allows for the cultivation of a wide variety of plants and crops. In comparison to conventional farming methods that rely on soil, hydroponic farming often results in superior harvests in terms of quality, flavour, and nutritional content. Worldwide, in both developed and developing nations, this cultivation is becoming more popular because to its low cost, lack of diseases, and environmental friendliness. In areas where suitable cultivable land is in short supply, it has the potential to supplement high-altitude research and alleviate the shortage of arable land. To fulfil the future nutrition requirement on a worldwide scale and cultivate a wide variety of fruits, vegetables, and feed, hydroponics is the way to go. Hydroponics is a new technology that has the potential to feed the world's population in the future. 

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.387
GPT teacher head0.304
Teacher spread0.083 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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