Liquid detergent packets: Small, brightly coloured, convenient and hazardous!
Bibliographic record
Abstract
The Smiths are busy raising two preschool children and managing multiple responsibilities at home and at work. They juggle household chores and child care on evenings and weekends. Like most Canadians, they strive to provide a safe home environment for their children. Laundry products are stored on a high shelf with other household chemicals. One evening, while preparing to do the laundry, Mr Smith becomes distracted and leaves the laundry basket on the floor with a liquid detergent packet on top. The laundry is forgotten and the following day one of the toddlers picks up the colourful detergent packet. It fits easily into her palm, and moisture on her hand starts to dissolve the packet's membrane. She tries to chew it and she bursts the membrane, releasing concentrated liquid detergent into her mouth. She starts to cry, pulls the packet from her mouth and rubs her face and eyes, further spreading the liquid detergent.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".