Bibliographic record
Abstract
Die rund 105.000 km² große Gletscherfläche in den Hochgebirgen des nordamerikanischen Kontinents (ohne die Kanadische Arktis) befindet sich zu fast 90% in Alaska. Aufgrund ihrer großen Eismasse besitzen die Gletscher Alaskas durch den möglichen Beitrag zum Meeresspiegelanstieg von ca. 5,5 cm eine globale Bedeutung. Der starke Temperaturanstieg verursacht bereits heute einen deutlichen Rückgang der Gletscher. In den Hochgebirgen im westlichen Kanada spielen die Gletscher vor allem als Schmelzwasserlieferanten für die umliegenden Regionen eine Rolle. Auch sie zeigen durch den Klimawandel deutliche Verluste, vor allem in den weiter im Binnenland gelegenen Rocky Mountains. Die Gletscher des zusammenhängenden Staatsgebiets der USA machen weniger als 1% der gesamten Fläche der Hochgebirgsgletscher in Nordamerika aus. Sie besitzen jedoch trotz ihrer geringen Ausdehnung erhebliche Bedeutung für die Hydrologie der jeweiligen Region. Der starke Temperaturanstieg und teilweise abnehmende Niederschläge haben bereits heute die Gletscherflächen, aber auch die Schneebedeckung, deutlich zusammenschmelzen lassen und werden bis 2100 zahlreiche Gletscher zum Verschwinden bringen - mit erheblichen Auswirkungen für die Wasserversorgung vor allem in Kalifornien. <em><strong>Glaciers and snow in high mountains in North America: </strong></em>Almost 90% of the approximately 105,000 km² glacier area (without the Canadian Arctis) in the high mountains of the North American continent is in Alaska. Due to their large ice masses, the Alaska glaciers are of global importance for their possible contribution to the sea level rise of approx. 5.5 cm. The sharp rise in temperature is already causing a significant decline in glaciers. In the high mountains in western Canada, the glaciers primarily play a role as melt water suppliers for the surrounding regions. They too are showing significant losses due to climate change, especially in the inland Rocky Mountains. The glaciers in the contiguous U.S. territory account for less than 1% of the total area of high mountain glaciers in North America. Despite their small size, however, they are of considerable importance for the hydrology of the respective region. The sharp rise in temperature and, in some cases, decreasing rainfall have already caused the glacier surfaces, but also the snow cover, to melt together significantly and will cause numerous glaciers to disappear by 2100 - with considerable effects on water supply, especially in California.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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".