MétaCan
Menu
Back to cohort
Record W4403732951 · doi:10.53555/sfs.v10i3.3116

From Waste To Wealth: The Potential Of Fish-Based Fertilizers In Crop Production

2023· article· en· W4403732951 on OpenAlexvenueno aff
Mr. Shaik Sameer

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)CropFish <Actinopterygii>Crop productionEnvironmental scienceAgronomyAgroforestryFisheryAgricultural scienceBusinessBiologyEconomicsAgricultureEcology

Abstract

fetched live from OpenAlex

This research paper explores the potential of fish-based fertilizers as a sustainable alternative to synthetic fertilizers in crop production. With increasing concerns over environmental degradation and soil health, fish waste presents an underutilized resource that can enhance soil fertility and plant growth. The study examines the nutrient composition of various fish by-products, their effects on soil microbial activity, and the resulting impact on crop yield and quality. Experimental results indicate that fish-based fertilizers significantly improve soil nutrient levels, promote beneficial microbial populations, and enhance crop productivity compared to conventional fertilizers. Additionally, the economic viability of fish-based fertilizers is assessed, highlighting their role in reducing waste and creating value in local agricultural systems. This paper concludes that integrating fish-based fertilizers into agricultural practices can contribute to a more sustainable and circular economy, benefiting both farmers and the environment.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.182
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.139
GPT teacher head0.279
Teacher spread0.140 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Survey in Fisheries SciencesSame topicInnovations in Aquaponics and Hydroponics SystemsFrench-language works237,207