Bibliographic record
Abstract
Flight crew, including full-time flight attendant and pilots spend an average of 700-10001 hours at altitudes of 10 000 m or higher in a given year. Given the number of hours spent in the air by cabin crew and pilots and the increasing number of frequent flyers, there has been increased concern on the health effects of cosmic radiation. Many countries now even recognize flight crew as occupationally exposed workers2. This research project will investigate the accumulated radiation exposure from a return trip from Toronto to Tokyo. It will discuss what research has been conducted to understand the risks that these workers and frequent flyers face as well as what the perceived and understood risks by both groups are. Data on perceived risks were collected via a questionnaire and actual risks were gathered using published literature. Cosmic Radiation Cosmic radiation consists of high energy particles originating from the sun. These high energy particles interact with the earth’s upper atmosphere creating a shower of lower energy particles. At higher elevations, exposure to cosmic radiation is greater when compared to those received at sea level. At sea level, the major component of cosmic radiation is muons while at higher altitudes cosmic radiation is dominated by neutrons, electrons and protons3.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".