Review and assessment of environmental impacts of ecological disasters on biodiversity in Anambra state, Nigeria
Bibliographic record
Abstract
Anambra State of Nigeria as well as other neighboring States and most of the other African countries suffer from major ecological disasters that pose much negative environmental effects on Biodiversity; that have also resulted in terminal changes on the lives of plant and animal species in the total environment as glaringlymirrored from Geological and Environmental Sciences field and laboratory studies and research. Climate change that results through natural and anthropogenic activities into high temperatures, heat waves, wind/sand/dust storms, excessive aridity, heavy rainfall, flooding, soil and gully erosion and landslides; environmental pollution and contamination; desertification; deforestation and urbanization; hunger, poverty and disease; greed, ignorance, poor professional attitude, fraud and corruption are some of the major environmentally-destructive factors that adversely-derail Biodiversity resources. Many varieties of plant and animal species and wildlife have been terminally-lost; by which all losses affecting parts of the Tropics of African countries are trending fast to an emerging regional biotic extinction within this Holocene (Recent) times. The present attitude by governments and people of all affected areas including Anambra State as a case example to Biodiversity losses is of a laissez-faire attitude and unscientific nature; officials do not seem to care. Also the public does not seem to care on the outcome. National governments, national and international aid agencies, institutional and corporate bodies, professionals and other individuals must change their attitude and acts to proffer better understanding to problems-solution and provide more moral and intellectual support and funding to experts and professionals for studies, research and effective local, national and regional control measures to check the massive terminal losses in Biodiversity in the environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".