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
Souki Mansoor is a dynamic force at the intersection of AI, creative direction, and social impact.As founder of the consultancy Bell & Whistle, she guides leaders and creatives in leveraging generative technology for positive change, working to reshape how we perceive AI in society and our daily lives.Coming from a rich decade-long background in nonfiction filmmaking, Souki's work has graced Sundance, Tribeca, and TED and can be seen today on Netflix, HBO, and Showtime, with her directorial debut "Firelei Baez" garnering critical acclaim and a Best Director award.A growing voice in the AI community, she's spoken at Cannes Lions on AI in Creativity and DEI, UTA's AI Symposium, USC's School for Cinematic Arts, Runway's AI Film Festival, Hollywood's AI On The Lot, and RealScreen West.When not playing a friendly neighborhood tech sherpa or falling into generative vortexes, she finds delight in nibbling spoonfuls of cashew butter, learning to pull the perfect espresso shot, and life with her husband Axel and their 63 houseplants.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it