Development of Needle Trap Technology for On-Site Determinations: Active and Passive Sampling
Bibliographic record
Abstract
This study presents a thorough evaluation of new prototypes of extended tip needle trap devices (NT), as well as their application to in situ sampling of biological emissions and active/passive on-site sampling of indoor air. A new NT prototype was constructed with a side hole above the sorbent and an extended tip that fits inside the restriction of the narrow neck liner to increase desorption efficiency. New prototype needles were initially packed with divinylbenzene particles at SGE Analytical Science for the purpose of studying biogenic emissions of pine trees. Prior to their final application, they were evaluated in terms of robustness after multiple use (n > 10), as well as amount extracted of volatile organic compounds (VOCs). An ANOVA test for all the probes showed that at a 95% level of confidence, there were not statistical differences observed among the 9 NTs tested. In addition, the needles were also packed in laboratory with synthesized highly cross-linked PDMS as a frit to immobilize carboxen (Car) particles for spot sampling. For passive sampling, the needles were packed with Car particles embedded in PDMS to simplify calculations in passive mode. The use of NTs as spot samplers, as well as a passive sampler under controlled conditions in the laboratoryyielded a relative standard deviation of less than 15%. Finally, a new, reusable and readily deployable penlike diffusive sampler for needle traps (PDS-NT) was built and tested. Application of the PDS-NT in combination with NT-spot sampling toward the analysis of indoor air in a polymer synthesis laboratory showed good agreement between both techniques for the analyte studied, yielding averages of 0.03 and 0.025 ng/mL of toluene, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".