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
Story maps have emerged in recent years as online tools for telling stories in an interactive and dynamic way. They are used to represent places associated with the story being told, allowing audiences to follow in the footsteps of an explorer or migrant, retrace the evolution of a conflict, or better understand the impact of the mining industry on caribou migration, for example. By easily combining maps, text, images and multimedia content, story maps offer a valuable alternative for promoting maps, exploration books, postcards, photos, video recordings, and other items from our polar collections. Currently, there are a number of open and proprietary applications for creating story maps, including the one from Esri. \n \nThis paper explains how the Esri Story Map application was used to present documentation related to the Coppermine Expedition conducted in the Canadian Arctic by Sir John Franklin between 1819 and 1822. The purpose of the paper is to share our experience with the application, showcase its benefits and limitations, and describe the skills required.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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