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Record W2901046535 · doi:10.2478/pesd-2018-0045

Biodiversity Conservation and Strategies of Public Awareness. Case Study: The Natural Landscapes of Central Tunisia

2018· article· en· W2901046535 on OpenAlexaff
Islem Saadaoui, Christopher Bryant, Hichem Rejeb, Alexandru-Ionuţ Petrişor

Bibliographic record

VenuePresent Environment and Sustainable Development · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGeographySustainable developmentContext (archaeology)EcologyEnvironmental resource managementSpecies richnessBiodiversityPopulationEnvironmental planningSociology

Abstract

fetched live from OpenAlex

Abstract This research examines global issues concerning the development of mountain areas considered as territories difficult to manage. The case study area is part of the sub-region of High Alpine Steppes belonging to the Tunisian Ridge and reaching Tebessa Mountains in Algeria. The central question of this article is based on the analysis of the links between the representations produced by mountain landscapes and the construction of a border line that must meet the requirements of sustainable development. Eco-landscape determinants and the role of public authorities and population must be better defined so that the products of this space provide a better quality of life endowed with the alternatives of local and sustainable development. Our hypothesis is that the mountain areas of West Central Tunisia still have a real ecological potential little disturbed by a chimerical development, and can constitute assets for the territorial development of the area. The approach adopted by this work is a scoping audit based on the floristic richness and the monitoring of its spatiotemporal dynamics. The results of this research allowed us to draw rich conclusions; the phyto-ecology approach has shown a relative floristic richness that remains highly dependent on the climatic cycles and intervention of human action; this area must be considered as a priority of the public planning policies aimed at improving the quality of lives in these fragile zones in the context of sustainable development.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.030
GPT teacher head0.211
Teacher spread0.181 · 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
Published2018
Admission routes1
Has abstractyes

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