Bibliographic record
Abstract
A dream came true last J une when my husband John and I went to onUl, Manitoba, Canada, the most a ccessible Arctic area on the North l,'hll~can cont i nent.Our purpose was to photograph those amazing tra velers jP t return each year to nest in the tundra .fromas .faraway as the south- tb', ti p o! Africa and the Horn of South America .No bander , however , •~d resist the hope of some day knowing the travels o.f a bird banded OO it s Arctic nest.on To band in Churchill requires a special penni t and band s issued by tbe canadian Wildlife Service .Mr. F. H. Schultz of the Migra tory Bird s ~8tra tion was most helpf'Ul.and sent us a permit to net and band.t,,e bands were returned to the Canadian Wildlife Se rvice from the re.sand9d birds were reported on the Banding Schedule , Form J-860 , and a OO'W sent to the Fi.sh & Wildlife Service at Patuxent.Arriving in Churchill on 21 June, we were too late to see the mig- ration when va st numbers of birds going even .furthernorth stop .for11 ,veral day s of re st.The birds remaining were already s cattered in their territories and brooding eggs.Shore birds, which we usually see only in drab plumage, were beautitul in nuptial dress.Songs that can only be heard at the nesting site tUled the air with new and lovely melody.It was also most amusing to btar "Hee-haw hee-haw" as an ending to the gurgling flight song of the Stilt Sandpiper.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".