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Record W4387169497 · doi:10.53555//sfs.v10i3.1647

Role of Biopestcides and Biofertilizer in Sustainable Agriculture

2023· article· en· W4387169497 on OpenAlex
Nabi Ullah, Tayyaba Bari, Adeel Ali, Hira Fatima, Sumaira Salahuddin Lodhi, Asia Noureen, Iqra Munir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Agricultural Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBiopesticideAgricultureSustainable agricultureBiofertilizerBusinessEnvironmental economicsBiotechnologyEnvironmental resource managementEconomicsPesticideBiologyEcologyAgronomy

Abstract

fetched live from OpenAlex

The intersection of environmental responsibility, economic viability, and agronomic innovation is sustainable agriculture. This study focuses on the crucial functions of biopesticides and biofertilizers as it explores the complex relationships among the aspects of sustainable agriculture. In order to understand the complex interplay between environmental, economic, and agronomic aspects, the study includes correlation analysis and reliability testing. The correlation analysis reveals complex patterns, such as the inverse relationship between "Pesticide Residue" and "Biopesticides," which supports the viability of biopesticides for residue management. The relationship between "Net Profits" and "Biopesticides" is favorable, underscoring the financial advantages of using sustainable methods. The reliability analysis supports the validity of the study's conclusions, and the survey instrument's robustness is supported by a high Cronbach's Alpha coefficient ( a = 0.82). The report summarizes findings, underlines the interplay of factors across dimensions, and provides policymakers with useful takeaways for promoting environmentally friendly and financially successful farming techniques. The study adds a thread to the complex web of sustainable agriculture while acknowledging its limitations and outlining potential directions. It emphasizes the significance of comprehensive approaches to solving current agricultural problems.

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.

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)0.004
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 score0.023
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.228
Teacher spread0.189 · 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