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Record W2955328482 · doi:10.35691/jbm.4102.0009

Biodiversity Assessment and its Effect on theEnvironment of Shakarparian Forest

2014· article· en· W2955328482 on OpenAlexaff
Inayat Ullah Malik, Abul Hasan Faiz, Fakhar -i-Abbas

Bibliographic record

VenueJournal of Bioresource Management · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsNutrasource
Fundersnot available
KeywordsBiodiversityLantana camaraFaunaGeographyLantanaRecreationWildernessEcologyFlora (microbiology)ForestryAgroforestryBiology

Abstract

fetched live from OpenAlex

Shakarparian is known for its scenic beauty and wilderness and has a significant recreational value. It is a part of Margalla Hills National Park (MHNP), Islamabad and can be a good recourse to conduct various environmental studies. This study was aimed to explore the overall biodiversity of Shakarparian forest in terms of flora and its associated fauna. Phytosociological survey was carried out in order to identify the existing plant communities. The plant associations were then correlated to the existing fauna of the area. The results will provide the baseline data to support further studies on biodiversity analysis of ecologically rich natural recourse base of our country. A total of 155 Animal species have been observed in the study area. Out of these species 23 species of Mammals, 104 of Birds, 22 of Reptiles and 6 species of Amphibians have been recorded. The dominating plant species of the zone are Cassia fistula, Carrisa apeca, and Lantana camara.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2014
Admission routes1
Has abstractyes

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