Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper explores the philosophical implications of machine learning text-to-image synthesis in a practice-based phenomenology of the computational poetics of a visual art process. It is hypothesized that artificial intelligence (AI) facilitated reflective image development fosters an anticipatory aesthetics in creative interactivity. The concept of AI-mediated “perspectival affordance” is introduced and its application to affective computing design emphasized. It is proposed that positioning intelligent systems as collaborative creativity tools promotes a dynamic interplay that envisions creativity as an anticipatory system, conceived of as those systems where exchange between artist and tool is mediated by future-oriented affective projection upon the system. The paper aims to establish a cognitive framework for AI-mediated creativity grounded in anticipatory interactivity, enhancing understanding of embodied cognition as mediated by AI in human-centered creativity support systems.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 0.000 |
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 it