Bibliographic record
Abstract
Andy Warhol famously quipped that in the future everyone would have 15 minutes of fame. He never mentioned that to obtain your moment in the spotlight you might have to acquire Brad Pitt's cheekbones or Pamela Anderson's breasts. I Want a Famous Face , a new MTV series, features seven individuals hoping to acquire the famous face of a pop star (www.mtv.com/onair/i\_want\_a\_famous\_face). Two participants, Mike and Matt Schlepp, conclude that their lives would improve if they acquired Brad Pitt's looks. To resemble Pitt, the brothers undergo rhinoplasty,receive chin implants, and obtain porcelain veneers. Sha is an aspiring model; she wants Pamela Anderson's physical features. She receives breast and lip implants and undergoes liposuction. Mia works as a Britney Spears impersonator; she wants Spears' “perky breasts.” Jessica, a transsexual formerly known as Michael, receives breast implants, cheek implants, and an eyebrow lift. She wants to resemble Jennifer Lopez. Jennette submits to a body lift after already undergoing gastric bypass surgery. She wants Kate Winslet's “full-figure” look. …
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".