Bibliographic record
Abstract
Veterinary clinicians often encounter with foreign body ingestion in domestic dogs. Accumulation of treatment information and epidemiological data about these cases could lead development of methods for prevention and enlightenment for dog owners. So far, these incidents are regarded as carelessness by dog owners, and veterinary clinicians did not show concrete directions for prevention of these incidents for owners. In this study, we analyzed animal health insurance claims data of these incidents in dogs and collected preventive findings about the cases from clinicians and owners using the internet research.Insurance claims data were used for analysis of the prevalence of these incidents in dogs. Total of 252,414 dogs which contracted Anicom animal health insurance from April 1 2009 to March 31 2010 were used as source data for analysis. 5,708 dogs cases were claimed as incidents caused by foreign body ingestion (total claims were 8,296 cases). Difference of prevalence of these incidents between ages is significant. 4.4% (2,728 dogs/61,448 dogs) for puppies under one year of age, 2.5% (736/29,215) for 1 year old, 1.8% (620/34,616) and under 1.5% for 3-10 years old. The average of prevalence for total dogs was 1.7%. Especially in puppies under one year of age, among top 17 breeds of insured dog, the prevalence of foreign body ingestion was 7.1% for French Bulldogs, 6.8% for Golden Retrievers, 6.0% for Cavalier King Charles Spaniels, 5.5% for Papillons, Labrador Retrievers, and 4.5% Toy Poodle. These breeds showed higher prevalence than the average (4.4%) for all breeds. For these breeds with higher prevalence materials/objects (substances) causing these incidents should be removed. The internet research with clinician prevailed that possible substances causing incidents (plural answer available) were some kinds of strings, seeds of fruit and plum pickles, medical supplies, pebble, grains of sand, some kinds of cloth like socks, towel and dust-cloth. Over 84% (145/172) clinicians reported that they encountered these incidents caused by above mentioned objects. Even 27 death cases were reported by strings, 16 cases by medical supplies and 13 cases by kinds of cloth. These objects/materials should be removed from dogs particularly. Death cases by accidental ingestions were also reported in dogs by poisoning of ornamental lily (12 cases), chocolate (9 cases) and onion (4 cases). The internet reserch for pet owners showed that over 90% of owners knew toxicity with chocolate and onion but only 29% of owners knew risk of poisoning with lily.Incidents caused by foreign body ingestion is very dangerous behavior inducing death in dogs, and careful monitoring of these incidents should be carried on with all concerned veterinary medicine.
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 | 0.015 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".