Bibliographic record
Abstract
Chabon, Michael. The Astonishing Secret of Awesome Man. Illus. Jake Parker. New York: Balzer & Bray, 2011. Print. Pulitzer Prize-winning novelist Michael Chabon recounts an archetypal small boy’s fantasy life as superhero Awesome Man. Equipped with all the requisite SuperPowers, including positronic-ray-blasting vision and a “thermovulcanized protein-delivery orb,” young Awesome Man, accompanied by Moskowitz, the Awesome Dog, does battle against the forces of darkness, including talking mutant Jell-O from beyond the stars. After vanquishing Professor Von Evil and his antimatter Slimebot, the young hero battles his arch-nemesis, the Flaming Eyeball, and henchmen Red Shark and Sister Sinister. Returning to his “Fortress of Awesome, deep at the bottom of the deepest, darkest trench under the Arctic Ocean,” he finds his mother, the only one aware of his secret identity, awaits his return in the kitchen to offer him a restorative serving of cheese, crackers, and chocolate milk. Chabon’s thoroughly derivative story line, familiar at least since Super Man’s 1939 debut in Action Comics No. 1, is only redeemed by Jake Parker’s imaginative and charming illustrations. Adults reading this slight effort to children will at least be afforded a chuckle over Moskovitz, the Awesome Dog, named in honour of one of Sci-Fi’s most prominent students and proponents. Recommended with reservations: 2 out of 4 starsReviewer: Merrill DistadMerrill Distad is Associate University Librarian (Research and Special Collections Services) and University Archivist, University of Alberta, and is the co-editor of Peel’s Bibliography of the Canadian Prairies to 1953 (Toronto, 2003). He is the author, most recently, of The University of Alberta Library: The First Hundred Years, 1908–2008 (Edmonton, 2009).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 0.018 |
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".