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Record W4389030425 · doi:10.5376/ijh.2023.13.0012

Effect Evaluation of the Agricultural Waste on Improving Growth of Potted Sunflower (<i>Helianthus annuus</i>)

2023· article· en· W4389030425 on OpenAlex

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

VenueInternational Journal of Horticulture · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsSunflowerHelianthus annuusAgricultureAgronomyEnvironmental scienceHorticultureBiologyEcology

Abstract

fetched live from OpenAlex

This review aims to evaluate the effect of agricultural waste on the growth of potted sunflowers.The rational utilization of agricultural waste is an important approach to address environmental issues and enhance agricultural sustainability.By comprehensively analyzing the findings and outcomes of relevant studies, this review explores the potential application value of agricultural waste in sunflower cultivation.Furthermore, it presents recommendations for further research and future prospects.These include comparing the effects of different types of agricultural waste on sunflower growth, delving into the mechanisms of agricultural waste, considering the comprehensive impact of environmental factors, and assessing the feasibility of practical applications.This study provides guidance for exploring future research directions and contributes important theoretical and practical value to promote the sustainable utilization of agricultural waste and the sustainable development of agricultural production.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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