Common Sources of Accidents in Kitchen Areas of Urban Households in Plateau State
Bibliographic record
Abstract
The study was designed to investigate the common sources of accident in thekitchen area of urban households in Plateau State, based on four types ofhousing units. Four specific purposes guided the research work. The studyadopted a descriptive survey design. The population for the study was madeup of 490,643 households. The sample for the study was 1,008 homemakersdrawn from the population of study through a multi-stage samplingtechnique. A structured questionnaire was used as the instrument for datacollection. Mean was used for data analysis. The findings revealed 16common sources of accidents in houses on a separate stand, 20 commonsources of accidents in flat in block of flats, 20 common sources in detachedhouses and 22 common sources in let-in houses. The study recommendssafety awareness creation campaign on common sources of accidents amongurban households in Plateau State based on all the functional areas of thehome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".