Paradigm Shift in Protective Barrier Covering Implements for the Endemic Phase of Corona Virus and Routine Airborne Pollutants: The Game Changer Approach - Phase Three Category
Bibliographic record
Abstract
This article presented a possible protective solution to the diverse health problems associated with human beings inhaling routine anthropogenic airborne particulates and micro-organisms by introducing some regular user friendly barrier covering implements i.e. narrows it down to zero pollutant inhaled for each person’s health care protection via the introduction of cosmetic-style barrier coverings, for the individual sense organs (i.e. nose-mouth-eye). Comprehensively, the atmosphere air is a mixture of several gases, consisting of three main components (78% nitrogen, 21% oxygen, and 1% argon), water vapor, trace gases such as the noble gases (neon, helium, krypton, and xenon); greenhouse gases (carbon dioxide, methane, nitrous oxide, and ozone); and the other gases such as hydrogen, iodine, carbon monoxide, ammonia, nitrogen dioxide, and sulfur dioxide, etc. Furthermore, particulate matter (PM) a mixture of solid particles and liquid droplets, such as dust, dirt, soot (a.k.a. black carbon), smoke, and smog-causing pollutants such as oxides of nitrogen (NOx), oxides of sulfur (SOx), are regularly being released into the atmosphere by human activities (anthropogenic sources). Along with volatile organic compounds (VOCs) i.e. chemical gases released from solid and liquid chemical products such as detergents, pesticides, printer supplies, adhesives, furniture, electronics, paints (and many other products), gasoline vapors, power plants and automobile exhaust, re-occurring wildfires and bush burning in different parts of the world (e.g. Canada, Brazil, California, etc.). Specifically, the June 2023 Canadian wildfire, whose smoke drifted into the northeast United States, and then temporarily made New York City “the most polluted city on the planet”, plus, the occasional air borne viruses and bacteria diseases (particles and respiratory droplets), during pandemics e.g. influenza, corona virus disease 19 (COVID-19), the common respiratory syncytial virus (RSV-a seasonal virus, characterized by variable epidemiology, depending on geographic area and climate) that share many similar symptoms as corona virus, etc. Most notably, this July 22, 2023 Erika Edwards report on “tripledemic” quoted Dr Mandy Cohen (director of the Centers for Disease Control and Prevention), as saying that the American people are expecting to have three bugs out there, “three viruses: COVID, of course, flu and RSV”. This means that many Americans will be urged to get three different vaccinations this fall: COVID, RSV and the annual flu shot. “But that will be a challenge for the health care system, (said Dr. William Schaffner, an infectious diseases expert and professor of preventive medicine at Vanderbilt University Medical Center), at a time when there’s already vaccine fatigue”. The pollutants and greenhouse gases (GHGs- CO2, CH4, N2O, O3, etc.) do not only contributing to climate change (e.g. global warming the emphasis in my first and second articles) but are also the major air, water, and soil pollution that already afflictsmany cities/countries globally today. Air pollutants with the strongest evidence for public health concern include particulate matter (PM), ozone (O3), nitrogen dioxide (NO2) and sulfur dioxide (SO2).
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".