Bibliographic record
Abstract
Chapter two begins with background information on the making of the Broadway musical Camelot by Frederick Loewe and Alan Jay Lerner, the team behind My Fair Lady. Jack Warner, intent on repeating the great success of Warner Bros.’ film version of My Fair Lady, purchased film rights to Camelot for a huge $2 million. Warner hired Joshua Logan, with Broadway and Hollywood credentials, to direct. Richard Harris was cast as King Arthur, Vanessa Redgrave as Queen Guenevere, and Franco Nero as Sir Lancelot. None among the principal cast had significant musical accomplishments. John Truscott, who had never designed a film, was brought on as art director. He showed an attention to lavish detail that would skyrocket Camelot’s production budget. Camelot was partially shot among medieval castles in Spain, but the cast and crew came back with surprisingly little footage. The chapter finishes with 74-year-old Jack Warner selling his shares in Warner Bros., turning to studio over to a Canadian film distribution company.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.108 | 0.081 |
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".