Detection of antibiotic residues in leg quarter of chickens slaughtered in accredited poultry dressing plants in Nueva Ecija, Philippines
Bibliographic record
Abstract
Antibiotic residues in consumable products pose health risks by contributing to antibiotic-resistant bacteria (ARBs), antibiotic-resistant genes (ARGs), and teratogenic and carcinogenic effects. Regular screening of livestock products allows monitoring of these residues in humans. This study aimed to determine the presence of six antibiotic class residues (beta-lactams, aminoglycosides, quinolones, sulfonamides, macrolides, and tetracycline) and multidrug residues in chicken leg quarters (CLQs) from an accredited Poultry Dressing Plant (PDP) in Nueva Ecija, Philippines. Thirty CLQs were collected from six PDPs in Nueva Ecija. Six muscle tissue specimens from each sample were screened for antibiotic residues through microbial inhibition tests at the National Meat Inspection Service (NMIS) Reserve Officers' Training Corps (RTOC) Regional III Laboratory Division, San Fernando, Pampanga. An inhibition zone ≥2 mm indicated a positive result. Screening showed no samples tested positive for any residue, and multi-drug residues were absent. No CLQs contained residues that exceeded the Maximum Residue Limit. CLQs from accredited PDPs in Nueva Ecija contained no antibiotic residues. These results may be due to strict antibiotic regulations, good veterinary supervision on source farms, and proper withdrawal periods.
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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".