Feral <i>E</i>. <i>ferus</i> in a range of different habitats.
Bibliographic record
Abstract
<p>Feral <i>E</i>. <i>ferus</i> inhabit areas worldwide with a wide range of habitats and climates, including Oostvaardersplassen, the Netherlands (<b>A</b>) (Credit: Eva Maria Kintzel and I Van Stokkum); tropical wet and dry seasons in Los Llanos, Venezuela (<b>B</b>) (Credit: Victor Ros Pueo); the Mongolian steppe in Hustai National Park, Mongolia (<b>C</b>) (Credit: Usukhjargal Dorj, Hustai National Park); the deserts of central Australia, western North America and Namibia (<b>D</b>; <b>G</b>; <b>L</b>) (Credit: Pernille J. Naundrup; Bureau of Land Management, USA; Telane Greyling); logged forests and snow covered winters in Alberta, Canada (<b>E-F</b>) (Credit: Bob Henderson); moorlands in Dartmoor, England (<b>H</b>) (Credit: Mark Robinson); feeding in the sand dunes and saltmarshes at Assateague Island, Maryland and Virginia, USA (<b>I-J</b>) (Credit: National Park Services, USA; Fritz Geller-Grimm, CC BY-SA 2.5); and in the mountains of Galicia, Spain (<b>K</b>) (Credit: Victor Ros Pueo).</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.186 | 0.005 |
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; both teacher heads agree on what is shown here.
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".