From Above, From Within: The Transformative Power of Travel and a Shift in Perspective
Bibliographic record
Abstract
My artistic journey has been profoundly influenced by my travelling experiences, affecting both my inspiration and personal growth while defining my artistic identity. Living and studying in the United Arab Emirates, Jordan, the United States, and Canada have broadened my cultural perspective and vision. As I traverse different landscapes, I perceive myself as a molecule within the vastness of the world, intricately connected to the surrounding environment. This immersion informs my approach to landscape painting, serving as a visual record of my observations, interpretations, and imaginations. Each brushstroke reflects the dynamic energy and vibrant shifting colours encountered during my journeys, documenting personal growth and artistic evolution. Through my landscapes, I endeavor to capture both the dynamic energy of nature and the emotional resonance it evokes, conveying the transformative power of travel and the profound connection between self and surroundings. In this thesis, I will delve into the evolution of my artistic journey in landscape painting, evoking the visceral experience of the scene rather than presenting a straightforward, easily interpretable narrative.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".