Analysis of a Survey Database of Pet Food Induced Poisoning in North America.
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.
Bibliographic record
Abstract
Following the outbreak of pet food-induced nephrotoxicity in March 2007, a voluntary online survey of all AAVLD-accredited laboratories, commercial laboratories, and veterinary clinics across North America was conducted. There was no information on toxicity of melamine or factors affecting the disease outcome following exposure to melamine in pets. Data were collected from affected pets to learn about the disease outcome and the affected pet population. The web-based electronic survey used the online tool, SurveyMonkey™. Data were collected between April 5 and October 31, 2007. Four hundred fifty-one cases of 586 reported cases met the criteria for inclusion in the study. Most reported cases were from California, Texas, Michigan, Florida, and Ontario. Of the 451 cases, 424 were reported as affected. Of these, 278 cases (65.6%) were cats and 146 (34.4%) were dogs. A total of 278 pets (171 cats and 107 dogs) were reported to have died (a ratio of 1.6:1). However, within species, there was a higher percentage of deceased dogs (73.3%) than cats (61.5%). Of the affected pet population, older male cats with preexisting disease conditions were more likely to be deceased. Analysis of the pets in this large database of naturally affected pets yielded interesting findings. It showed that more cats than dogs were affected and also that preexisting renal diseases and old age predicted the most severe outcome (death or euthanasia) than any other factors.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.014 | 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 it