Bibliographic record
Abstract
This chapter recounts the author's visit to the Charles Himes cottage, focused on finding correspondence and photos from the crew's families. Reference to these in newspaper accounts from 1944 had hinted at what the families had endured—or in one instance failed to endure—as the grand hope of their boys being found alive succumbed to the modest expectation that their bodies would be recovered. The chapter emphasizes that it is difficult to conjure events that have drifted to the fringes of conscious memory or pay homage to a tomb that can't be found. Yet, as the chapter argues, it is safe to say that in 1944, the memory of Gertie's crew was painfully fresh and diligently tended by mothers and fathers, sisters and brothers, their grief anchored to a uniquely human compulsion to know how and where things came to an end, and lay to rest the bodies of their loved ones. Nearly eighty years later, the story of Gertie waits to be made whole. The chapter considers the exhaustive administrative process for the National Oceanic and Atmospheric Administration's (NOAA) Lake Ontario Marine Sanctuary. The sanctuary designation, would, according to the final assessment from NOAA, “provide a national stage for promoting heritage tourism and recreation” and “ensure future generations can learn about and explore these underwater treasures.”
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.032 |
| Scholarly communication | 0.015 | 0.024 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".