Keys and the Crisis in Taxonomy: Extinction or Reinvention?
Bibliographic record
Abstract
Dichotomous keys that follow a single pathway of character state choices to an end point have been the primary tools for the identification of unknown organisms for more than two centuries. However, a revolution in computer diagnostics is now under way that may result in the replacement of traditional keys by matrix-based computer interactive keys that have many paths to a correct identification and make extensive use of hypertext to link to images, glossaries, and other support material. Progress is also being made on replacing keys entirely by optical matching of specimens to digital databases and DNA sequences. These new tools may go some way toward alleviating the taxonomic impediment to biodiversity studies and other ecological and evolutionary research, especially with better coordination between those who produce keys and those who use them and by integrating interactive keys into larger biological Web sites.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.026 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".