Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Alaska is the last frontier and final destination for the National Science Foundation-supported EarthScope USArray Transportable Array (TA) project. The goal of this project is to record earthquakes and image the structure of the North American continent. The Alaska TA consists of 283 broadband seismic stations evenly spaced about 85 km apart to cover the state of Alaska and into western Canada. The sensor emplacement technique and station design were developed specifically for superior performance—both in terms of seismic noise levels and station durability. This technique and design were used for the 194 new stations installed as well as the 32 existing broadband stations that were upgraded. Trial stations were installed in 2011–2013 as part of a process to test and refine the installation design. The main deployment began in 2014 using the final station design and was completed in 2017. From 2018 through 2020, Incorporated Research Institutions for Seismology (IRIS) operated the Alaska TA by performing servicing, station improvements, and data quality monitoring. High data return was maintained throughout, though some stations had lower real-time data delivery in winter. 110 TA stations are expected to transition to other operators in 2019 and 2020, and the data from these are openly available under new network codes. The last 84 stations are expected to be removed during the 2021 field season to close out the TA project. The Alaska TA was installed safely despite a challenging environment and has been operated to maximize the continuity and quality of data collected across a vast geographic region, enabling exciting scientific research for years to come.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 it