Thoroughly Modern Millie (2010 program)
Bibliographic record
Abstract
Performed November 5-6, 2010. Cast:Millie Dillmount: Elizabeth HarrellJimmy Smith: Nate WhiteMiss Dorothy Brown: Amanda LaneTrevor Graydon III: Sam BarkerMrs. Meers: Mary McBrideChing Ho: Blake HunterBun Foo: Josh LittleMuzzy Van Hossmere: Alycia HaynesMiss Flannery: Cassie Bennett Hotel Priscilla Girls:Lucille: Eric GardnerCora: Gabriella MarcelliniGloria: Lauren SchlabachRita: Jami WinfreyAlice: Logan KaysRuth: Allison MusslewhiteEthel Peas: Kaelyn Tavernit Ensemble: Jonathan Aders, Abby Anklam, Seth Bowden, Molly Brooks, Emily Davis, Rachel Filbeck, Erica Gardner, Christopher Hanes, Nathan Howell, Tiffany Jones, Blake Krogull, Joshua Lundin, Jonathan Marlin, Erin McBride, Stephen McBride, Katie McCafferty, Carson McGill, Sisan McNeil, Austin Niblett, Aleece Overturf, Lisa Pavlova, Tyler Perring, Bryan Phillips, Elizabeth Provencher, Jonathan Sherrod, Christa Smith, Grace Strickland, Aaron Tucker, RC Tucker, Morgan Tunnell, Victoria Tyer, Rily Walling, Emily Welfare, Megan West, Liz Willen, Aisleyn Wilson, Lauren Wilson, Tori Wisely, Conner Yates, and Rob Yates Vocalists: Grace Allen, Kittrell Camp, Barry Chenault, Emily Eads, Maggie Ellis, Michelle Heroux, Dillion Holden, Alex Leach, Parker Leasure, Neely McCoy, Hannah Robison, Jordan Simpson, Dustyn Stokes, and Rachel Swift
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.767 | 0.554 |
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".