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Record W2899885441 · doi:10.5539/jas.v10n12p34

Management and Final Disposal of Mango Waste in the State of Guerrero, Mexico: A Brief Review

2018· review· en· W2899885441 on OpenAlexvenueno aff
Miguel Angel Lorenzo-Santiago, A. L. Juárez-López, José Luís Rosas-Acevedo, J. R. Rendón-Villalobos, J. Toribio-Jiménez, Edgar García‐Hernández

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsnot available
Fundersnot available
KeywordsMangiferaProduction (economics)BusinessIntegrated pest managementWaste disposalEnvironmental protectionEnvironmental planningAgroforestryGeographyWaste managementEngineeringEnvironmental scienceBiologyEcologyEconomics

Abstract

fetched live from OpenAlex

One fruit trees crops with largest amount in Mexico is the mango (Mangifera indica L.). In 2017, Guerrero was the state with the highest production in the country. However, the waste generated after harvesting represents an environmental problem caused by high production and low opportunity in the national and international markets. Nowadays, there is no environmental policy to regulate this final waste disposal. Regularly, post-harvest waste has no value and most of the time, its disposal is inadequate. The lack of training and management knowledge, separation and use, has generated an imbalance in the environment, caused by inadequate elimination practices and excessive use of pest prevention activities, known as cultural control. The main objective of this review was to know about mango production in Guerrero State, its final disposal after harvest and the environmental impact generated by cultural control use.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.064
GPT teacher head0.310
Teacher spread0.245 · 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 designOther design
Domainnot available
GenreReview

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

Citations5
Published2018
Admission routes1
Has abstractyes

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