Bibliographic record
Abstract
You have accessThe ASHA LeaderInbox1 Jan 2012More on Toxicants William J. Blackley, and Sandie Barrie-Blackley William J. Blackley Google Scholar More articles by this author and Sandie Barrie-Blackley Google Scholar More articles by this author https://doi.org/10.1044/leader.IN4.17012012.38 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In Thank you for publishing Ms. Hepp’s article, “Protecting Children from Toxicants” (Nov. 22, 2011). Ms. Hepp clearly outlined the risks and made good suggestions for reducing them. Many of the toxins Ms. Hepp listed can be traced to one source: air pollution from biomass incineration. Biomass burning emits many of the same toxins as tobacco smoke, but it is often colorless and odorless. The absence of smoke is no guarantee of safety. Burning municipal waste and wood for energy, wrongly touted as “green” power, is increasing across the United States and is creating an entirely new source of dioxins and nanoparticles with multiple health risks including cancer, asthma, and neurological problems in children. Do you think the government will protect you through regulations? The U.S. government allowed lead in gasoline and paint, formaldehyde, asbestos, benzene, dry cleaning fluid, dioxins in Agent Orange, DDT and more. Its damage to humans is well documented. The American Academy of Family Practice, representing 94,700 physicians, last year issued a letter of concern about biomass burning because of the increased health risks to humans. For the health of your children, demand that your legislators incentivize truly clean energy sources such as solar, wind, water, and hydrogen fuel cells and stop the promotion of dangerous biomass burning. Meanwhile, if you see a smokestack burning wood (biomass), coal (fossilized biomass), or municipal waste (biomass), keep children far away from it if you can. William J. Blackley Sandie Barrie-Blackley Elkin, North Carolina Advertising Disclaimer | Advertise With Us Advertising Disclaimer | Advertise With Us Additional Resources FiguresSourcesRelatedDetails Volume 17Issue 1January 2012 Get Permissions Add to your Mendeley library History Published in print: Jan 1, 2012 Metrics Current downloads: 64 Topicsleader_do_tagasha-article-typesleader-topicsCopyright & Permissions© 2012 American Speech-Language-Hearing AssociationLoading ...
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.882 | 0.752 |
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".