Class III: Intensive Cultural Resources Inventory of up to 212 Acres, Cavalier Space Force Station, Pembina County, North Dakota
Bibliographic record
Abstract
Stell Environmental Enterprises, Inc. (Stell) performed a Class III: Cultural Resources Inventory of 196.89 acres (ac) managed by Cavalier Space Force Station (SFS) under subcontract agreement 1F-60506 with Argonne National Laboratories (Argonne). Argonne is the prime contractor under contract project EGYNA53201118. Prior to field work, Stell personnel visited the State Historical Society of North Dakota and performed a Class I: Literature Search of the Cavalier SFS and 1- mile buffer of the surrounding area. The literature search identified a total of eight cultural resources surveys conducted within the 1-mile buffer in and around the Cavalier SFS. These surveys resulted in the identification of five cultural resources consisting of one prehistoric lithic scatter, one historical homestead, and three historic architectural sites. The single cultural resource located within the installation boundary is the Cavalier SFS Perimeter Acquisition Radar (Site). All relevant information was incorporated into a research design that provided guidance for performing the cultural resources inventory under this contract. A pedestrian surface survey of the project area did not identify any cultural resources. Due to the project area being larger than 40 ac, Stell’s field efforts and results are presented in this full report.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.053 | 0.012 |
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".