2020 AAHA/AAFP Feline Vaccination Guidelines
Bibliographic record
Abstract
The guidelines are a consensus report on current recommendations for vaccination of cats of any origin, authored by a Task Force of experts. The guidelines are published simultaneously in the Journal of Feline Medicine and Surgery (volume 22, issue 9, pages 813–830, DOI: 10.1177/1098612X20941784) and the Journal of the American Animal Hospital Association (volume 56, issue 4, pages 249–265, DOI: 10.5326/JAAHA-MS-7123). The guidelines assign approved feline vaccines to core (recommended for all cats) and non-core (recommended based on an individualized risk–benefit assessment) categories. Practitioners can develop individualized vaccination protocols consisting of core vaccines and non-core vaccines based on exposure and susceptibility risk as defined by the patient’s life stage, lifestyle, and place of origin and by environmental and epidemiologic factors. An update on feline injection-site sarcomas indicates that occurrence of this sequela remains infrequent and idiosyncratic. Staff education initiatives should enable the veterinary practice team to be proficient in advising clients on proper vaccination practices and compliance. Vaccination is a component of a preventive healthcare plan. The vaccination visit should always include a thorough physical exam and client education dialog that gives the pet owner an understanding of how clinical staff assess disease risk and propose recommendations that help ensure an enduring owner–pet relationship.
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 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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.053 | 0.033 |
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".