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Urban Landscape Planning and Soil Variation in Nigeria: Lokoja as a Case Study

2012· article· en· W1953336716 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

VenueCanadian social science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Development and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsLandscapingVegetation (pathology)Distribution (mathematics)ColonialismTree plantingGovernment (linguistics)GeographyEnvironmental scienceAgroforestryEcologyArchaeologyBiology

Abstract

fetched live from OpenAlex

The legacies of the colonial masters of a well landscaped environment have been left to rot due to negligence and increase need for urban land for anthropogenic activities. This had led to recent attempts of revival by the government through tree planting campaigns, which have not yielded desired result. Soil factor have been found to be neglected in landscaping the urban environment, this have been attributed to failure of landscaping attempts in the study area. This research attempted to find the relationship between the vegetation species distribution and soil physical properties with use of spearman’s correlation coefficient. The findings show that relationship between vegetation species distribution and soil physical properties are not significant, this may mean that there are other factors that must be considered in determining why certain species of plant thrive in certain areas than the other. Key words: Soil degradation; Colonial legacies; Landscaping; Vegetation species

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.287
Teacher spread0.263 · 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