Bibliographic record
Abstract
The study of meteorites can give insight regarding the chemical composition that was present when the solar system was being created. The elements in meteorites have not undergone extensive changes since they were formed billions of years ago, so they are thought to resemble those on Earth before the formation of the hydrosphere. This can lead to information regarding the formation of the solar system, Earth, and consequently, life. Sulfur is of interest because it has essential roles in biochemistry and a prevailing theory regarding the origin of life is that it began in an iron-sulfur world. By determining the sulfur composition of meteorites and the isotopic ratios – ratio of atoms of the same element with different atomic masses – we hope to determine the processes behind for formation of the form of sulfur responsible for the creation of life. This first stage of the project was to perfect wet chemistry and analytical techniques to extract and quantify sulfur species from meteorites. The development of the techniques required reading research literature, testing, and altering the techniques while working with a meteorite simulant. Multiple extractions with different solvents were used to differentially separate the sulfur species based on their chemical and physical properties. These initial techniques have been modified and applied to other meteorites. They will continue to be improved upon. Faculty Mentor: Robert Hilts Department: Chemistry
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".