Bibliographic record
Abstract
Through integrating different forms of media, the creator is able to give their audience a unique, multi-sensory experience. In my honors thesis, I concentrated on combining sight and sound as a communication tool and to further engage the observer.\nThe first type of media I chose to include was original solo instrument, voice, and piano songbooks focusing on lyrical playing for student and amateur musicians. I have also created audio realizations of the songs through Finale, which I then organized into CDs with the intention that the musician could understand how the music sounds before practicing. I combined the visual notated music and audio files along with my original artwork covers to create a package that would both appeal to the audience and convey my character.\nThe second type of media I chose to incorporate is five slideshows of my artwork accompanied by five of my original compositions. In choosing both the artwork and the compositions to include, I wished to portray a glimpse into my artistic development from the beginning of college (and in some cases middle and high school) through my current state.\nThe third type of media I challenged myself to include was five movies accompanied by five of my original compositions. After much searching on the Internet, I realized my first question to myself should be "what message do I wish to convey?" I remembered that I had stumbled upon several videos from NASA a few months back that would be perfect to include. I have always been interested in astronomy, and by combining these two seemingly unrelated interests, I could connect the arts and sciences together, showing my audience not only who I am as a person, but also that no matter what field you choose to pursue, you can always integrate your other interests with it. After searching through my various compositions, I chose five musical works that I thought would embody and enhance the essences of the NASA video clips I had chosen.\nI have never really known "what I want to be when I grow up". In fact, I am constantly changing and may never know. However, through integrating these various forms of media and incorporating my different interests in music, art, and astronomy, it has taught me that I do not have to necessarily choose. As long as I keep my options open, I can instead use everything I learn and apply it to different areas of my life. This has been a great exercise in composing for different types of media and it has shown me where I have come from musically and artistically and where I am now. I do not know where life will take me, but I only wish it will let me inspire others to take this wonderful gift and follow their dreams fiercely and without hesitation.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.812 | 0.582 |
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; the direct Gemma label and the distilled Codex classifier 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".