Bibliographic record
Abstract
An important part of climate change education is an understandable and memorable presentation of components within the climate system. Here, we present the development of a learning tool clarifying glaciers with a focus on their association with climate. Images of glaciers and glacial features that resemble lower case letters were obtained by examining the range of satellite image types displayed on Google Earth’s virtual globe. Each letter-image of the alphabet was matched with a glaciological term starting with that letter, and describing the glacial feature or process in the corresponding image. The ensemble of images, terms and their definitions, was portrayed as a classroom educational poster. This Glacier Image Alphabet is a visually attractive and informative glossary of terms representing glacier processes, such as accumulation, ablation, and ice flow, as well as ice age and ice core records, and common glacier features and names. The poster contains a glacier distribution map, and is accompanied by an online component in Google Tour Builder to provide a more interactive geographical learning tool with expanded content. The Glacier Image Alphabet is aimed at senior high school and first year undergraduate students.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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; both teacher heads agree on what is shown here.
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".