Ground-water, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona: 1998
Bibliographic record
Abstract
Chemical concentration and water temperature are given only in metric units.Chemical concentration in water is given in milligrams per liter (mg/L) or micrograms per liter (µg/L).Milligrams per liter is a unit expressing the solute mass (milligrams) per unit of volume (liter) of water.One thousand micrograms per liter is equivalent to 1 milligram per liter.For concentrations less than 7,000 milligrams per liter, the numerical value is about the same as for concentrations in parts per million.Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (µS/cm at 25°C).Chemical concentrations in streambed sediment are given in micrograms per gram (µg/g) or micrograms per kilogram (µg/kg).Micrograms per gram is equal to parts per million (ppm).Micrograms per kilograms is equal to parts per billion (ppb). VERTICAL DATUMSea level: In this report, "sea level" refers to the National Geodetic Vertical Datum of 1929 (NGVD of 1929)-a geodetic datum derived from a general adjustment of the first-order level nets of the United States and Canada, formerly called "Sea Level Datum of 1929".
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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".