An examination of exposure and avoidance behavior related to second-hand cigarette smoke among adolescent girls in Canada
Bibliographic record
Abstract
The 50 % tissue culture infectious dose (TCID50) is still one of the most commonly used techniques for estimating virus titers. However, the traditional TCID50 assay is time consuming, susceptible to subjective errors and generates only quantal data. Here, we describe a colorimetric-based approach for the titration of Enterovirus 71 (EV71) using a modified method for making virus dilutions. In summary, the titration of EV71 using MTT or MTS staining with a modified virus dilution method decreased the time of the assay and eliminated the subjectivity of observational results, improving accuracy, reproducibility and reliability of virus titration, in comparison with the conventional TCID50 approach (p < 0.01). In addition, the results provided evidence that there was better correlation between a plaquing assay and our approach when compared to the traditional TCID50 approach. This increased accuracy also improved the ability to predict the number of virus plaque forming units present in a solution. These improvements could be of use for any virological experimentation, where a quick accurate titration of a virus capable of causing cell destruction is required or a sensible estimation of the number of viral plaques based on TCID50 of a virus is desired.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".