MARSHES-IN PHOTOS AND WORDS. Review of <i>Marshes: The Disappearing Edens</i> by Bill Burt
Bibliographic record
Abstract
Bill Burt has done it again. The author of two superbly illustrated books (Shadowbirds and Rare and Elusive Birds of North America) that were reviewed earlier in this journal, Burt has returned with another excellent book, this one focusing on marshes. Like his earlier books, Marshes features wonderful close-up views of many hard-to-photograph birds. Here, in addition, are grand images of marsh landscapes and other marsh denizens, especially plants. Burt best characterizes his own book, which he intends as "an evocation and exploration, rather than a catalog of marshland life." He tells of his 30 years spent prowling marshes of all kinds, all over North America, day and night ~like. His books display some of the results of his searches, both in word and wondrous photography. Burt ranges widely in his searches for marshes. Each of the seven chapters focuses on a marsh, or an area with marshes. He starts with his "home" marsh, in Connecticut. Then to Maryland and its Elliot Island marsh, then a fen near Douglas, Manitoba. One chapter touches on marshes of the southern Atlantic and Gulf coasts, where he finds pleasure in the saltmarshes of Virginia and New Jersey, and wonders why the people of Louisiana seem oblivious to the marshy pageantry that surrounds them.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.099 | 0.053 |
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".