Bibliographic record
Abstract
Oregon's mineral industry produced its second highest value of row minerals in 1960. Following a nation-wide economic trend during the year, the industry was off approximately $3 million from lost year's record-breaking high of $49.8 million, according to preliminary estimates mode by the U. S. Bureau of Mines. The heavy construction commodities, crushed stone and sand and grovel, reflected construction log and were responsible for most of the change from lost year. Metal mining, aside from nickel, was quiet. The state's only uronium mine and one of the two mercury producers shut down. Industrial mineral products showed both gains and losses as compared to the previous year. Cement production was up 12 percent while clays declined 15 percent and diatomite 3 percent. Pumice and volcanic cinders were up 9 percent and stone and s(;md and gravel were off 11 percent. Building stone activity was greatly increased over 1959. Two major tests for oil were conducted during the year. Construction of a natural gas pipeline from Camas, Washington, to Eugene, Oregon, provided the area with an important raw material basic to many industrial operations. A second pipeline extending from Alberta, Canada, to California was started late in the year. The line will make natural gas available to such points as Bend, Klamath Falls, Medford, and the Rogue River Valley. Pacific Power and Light Company conducted by-product tests
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.361 | 0.193 |
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".