IDENTIFICATION OF SOME CARCINOGENIC POLYCYCLIC AROMATIC HYDROCARBONS IN BANGLADESHI VEHICLES EXHAUST TAR BY GAS CHROMATOGRAPHY-MASS SPECTROPHOTOMETER
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
A more sensitive GC-MS method has been established for the determination of some carcinogenic polycyclic aromatic hydrocarbons (PAHs) in vehicles exhaust tar samples. The tar samples were extracted using dichloromethane (DMC): n-hexane solvent mixture. A multi-layer clean-up (silica gel/sodium sulphate) column was used, followed by glass fiber filter (GFF) paper. The method was successfully applied to determine a number of PAHs present in exhaust tar sample of different vehicles of the Atomic Energy Centre, Dhaka, Bangladesh. Keywords: Carcinogenic polycyclic aromatic hydrocarbons, vehicles tar samples, identification, GC-MS/MS
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it