Bibliographic record
Abstract
Skjold, Norway—The bullets were real. But fortunately for the Norwegian snipers, this was just an exercise. If it had been real combat, the enemy would have easily spotted the troops in the vast whiteness of the Arctic. The white camouflage uniforms didn’t match the ever-changing color of snow. The men’s breath and shadows were easily seen in the frost. And the extreme cold impaired the sharpshooters’ accuracy by influencing bullet speeds.It’s tough to wage war in the Arctic.As melting glaciers open up access to shipping routes and energy troves, countries with polar real estate are modernizing armies just in case. Severe cold is the last frontier in warfare, barring outer space, and the militaries of the United States, Canada, Denmark, Russia, and Norway are finding that the environment presents dangers as challenging as any enemy. When the mercury drops to 55 below Fahrenheit, ballistics malfunction, helicopters can’t take off, and vehicles stall. Men are prey to frostbite, avalanches, and snow blindness. Dogs can’t track mines or victims buried in drifts.“If you can survive and fight in the extremes of the Arctic, you can fight anywhere in the world,” says Lt. Col. Lars Sundnes, commanding officer of the Allied Arctic Training Center in the high reaches of Norway.But just surviving is formidable.Photographer Robert Nickelsberg and I spent nearly two weeks in the Arctic Circle with forces from Norway, Britain, and the Netherlands to observe training in the planet’s harshest climate. The journey began at a mountain bunker in Bodo and continued on to a helicopter battalion in Bardufoss, coastal operations in Harstad, and avalanche mapping and live fire exercises in Skjold. The constant takeaway was that proper clothes are as vital as nuclear submarines.The simplest choices, such as what to eat and wear, become critical, explains Sgt. John Rutherland, an instructor with the British Royal Marines. “If you’re up against a wet and cold enemy, you win, even if they have better equipment,” he tells a circle of men stoking fires in a frozen forest. Three months of training covers survival, mobility, and combat skills.Lessons start with layering clothing to mitigate the harsh elements. Men then learn to dig snow caves, slaughter reindeer, and fish through ice. They claw out of glacial lakes and drag 200-pound “casualties” like huskies on skis. They trek in deep snow with 100 pounds of gear on their backs.Briefings explain the climatic effects on equipment. Moving parts break, ice clogs optics, and batteries drain quickly. Moisture collects when going from cold to warm and back to cold, such as when entering and exiting a warm tent. Powder burns slower when cold, so artillery rounds can fall short of the desired impact area. Deep snow makes detonation of grenades less lethal as it absorbs much of the blast. Warm rounds dragging tough snow will jam or not feed at all in automatic weapons.Pilots practice landing helicopters in dreaded “white outs,” when swirling snow impairs depth of perception so you don’t know if you’re up or down. Soldiers are taught how to warm medical fluids, engines, and satellite technology with parachute covers and stoves.More than anything, they drill to watch over buddies. “You need to stay sharp in this environment. There’s no room for error,” explains Capt. Kris Lotveit of Norway. “We have a saying, ‘Don’t expect, inspect.’ It’s not good enough to ask a strong Marine with tattoos and big muscles if he’s okay. He will say, ‘Yes, sir.’ You have to check to see that his toes aren’t frozen.” In this Portfolio, Robert Nickelsberg chronicles the challenges that face Arctic warriors and how Western forces are overcoming them.
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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 | 0.001 | 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 | 0.001 | 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) | 0.003 | 0.001 |
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".