A vision for documenting and sharing knowledge in conservation
Bibliographic record
Abstract
A vision for documenting and sharing knowledge in conservationAs editors, we mark the launch of Conservation Science and Practice, a journal of the Society for Conservation Biology (SCB), with the following remarks framing the purpose and aspirations of the journal.Our aim is to share scholarship on and experiences of the practice of conservation.We define conservation practice as the application of conservation principles or theory across conservation issues, from planning and directly managing nature to influencing public policy and private behaviors-at scales from local communities to international governing bodies.We are striving for Conservation Science and Practice to be a forum for sharing lessons learned from research and practice to reciprocally informing and improving both arenas.The publication model for Conservation Science and Practice sees the editorial team make five commitments:
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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 | 0.333 | 0.298 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.027 | 0.095 |
| Scholarly communication | 0.079 | 0.133 |
| Open science | 0.020 | 0.078 |
| Research integrity | 0.048 | 0.037 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".