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Directrices para la gestión de residuos sólidos em ambientes de alta montaña

2013· dissertation· es· W4255818499 on OpenAlexaboutno aff
Omar Milton Romero Catacora

Bibliographic record

Venuenot available
Typedissertation
Languagees
FieldEnvironmental Science
TopicFinance, Taxation, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsTourismGeographyMunicipal solid wasteIdentification (biology)Statistical analysisEnvironmental planningEnvironmental resource managementEnvironmental scienceEngineeringWaste managementMathematicsArchaeology

Abstract

fetched live from OpenAlex

This study aims to analyze issues relating to the solid waste management in high mountain regions, from its generation, which is driven by the increase of tourism in these regions, to final disposal. This process of unbridled tourism is leaving a huge negative environmental impact on glaciers and in the headwaters of watersheds that supply regions located at the foot of the mountain ranges. An analysis of more sustainable patterns of tourism processes, guiding the analysis to the guidelines and alternatives for Integrated Solid Waste Management. The hypothesis of the study is based on a diagnosis of the current situation of solid waste generation in the mountains, a statistical analysis of the data, the improvement of the processes involved, it is possible to formulate guidelines for waste management, incorporating new technologies in waste management and the incorporation of social technologies on the adequacy of the proposed guidelines, to stop waste a problem. Were made early expeditions into the mountains to the characterization of the waste generated by expeditions in the Peruvian highlands and in the Canadian Rockies, was determined mountain tourism as the most powerful category, then statistical tests were performed for both primary processes, from measures of central tendency was found statistical inference data for a larger universe of data and with the same characteristics, then performed the analysis capacity of the two processes and the data was compared statistically and measures central tendency. From these data we proceeded to make the identification of variables that affect the generation of waste in the Peruvian process and proposes an improvement to the implementation of quality plans. Again expeditions were made following the proposed improvements to the process, new data were obtained from waste generation, became a statistical comparison of the data of ancient Peruvian process and details of the new Peruvian process. Were obtained from the final results of which were drawn the conclusions and recommendations of this study.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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