La misión rusa Arktika 2007 y sus implicaciones para el balance mundial de poder en el siglo XXI
Bibliographic record
Abstract
espanolEl derretimiento del hielo polar y los altos precios de los energeticos han abierto una oportunidad para Rusia, deseosa de adjudicarse una amplia porcion de territorio artico para aumentar su poder nacional en las esferas geopolitica, economica y estrategica. Estas ambiciones se reflejan claramente en la mision rusa Arktika lanzada para probar la validez de las exigencias de Moscu. Si dichas ambiciones se ven realizadas, ello pudiera ayudar significativamente a Rusia a recobrar su estatus de gran potencia. Sin embargo, Estados Unidos y Canada de ninguna manera desean ver cumplidas las aspiraciones rusas, debido al poder que este pais adquiriria. No obstante, aun es demasiado pronto para predecir que tan lejos estan dispuestos a ir. EnglishThe melting of the polar ice caps plus the high energy prices hace opened a window of opportunity for Russia, who seeks to obtain a large portion of Arctic territory in order to increase its national power in the geopolitical, economic and strategic spheres. These ambitions are clearly shown in the Russian mission called Aektika 2007, launched to collect supportive evidence of Moscow´s claims. If such ambitions are indeed accomplished in the long run, that could meaningfully help Russia regain its status as a great power. Nevertheless, the United States and Canada are not eager to see Russian aspirations fulfilled. However, it is still too soon to predict how far they are willing to go.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".