Bibliographic record
Abstract
Abstract Hundreds of otherwise normal people are passionate about an intriguing group of insects called tiger beetles (family Cicindelidae). These cicindelophiles or tiger beetlists can be found swinging insect nets to collect wary tiger beetles from sandy pine forests in Florida to alpine meadows in the Canadian Rocky Mountains. Others might spend hours crawling on elbows and knees in the piercing heat of an Arizona grassland for close-up photos of a ruby-red species. A few sit patiently on the white sands of a New Jersey beach taking notes about the mating behavior of a long-legged tiger beetle that is listed by the United States government as an endangered species. These activities and others unite a diverse group of tiger beetle enthusiasts, only a few of whom are professional entomologists. Tiger beetles elicit something more than a routine response to the necessities of employment. Note the highly enthusiastic and curious behavior of some lawyers, dentists, prison guards, railroad workers, and computer engineers who have found a life-long hobby in beetle watching.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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".