Turning setbacks into stepping-stones for growth in conservation paleobiology
Bibliographic record
Abstract
Conservation paleobiology is a cross-disciplinary field that utilizes the geohistorical record of past life on Earth to inform present-day decisions in conservation and restoration and assist in planning for future natural resource management. However, information on how past ecosystems and species responded to environmental change over decadal to millennial timescales is rarely incorporated into conservation and restoration decision-making. To heighten awareness among conservation and restoration practitioners of the relevance of geohistorical data and to bridge the gap between research and implementation in conservation paleobiology, we proposed a Research Topic titled “ Integrating Conservation Biology and Paleobiology to Manage Biodiversity and Ecosystems in a Changing World ”. The 21 articles subsequently published demonstrate the diversity and breadth of geohistorical information available to resource management and the challenges of translating these results into conservation practice and policy. Here we discuss the lessons we learned from editing the Research Topic and suggest a pathway forward for conservation paleobiologists who aspire to generate actionable research results to solve current problems in biodiversity conservation and ecological restoration.
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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 | 0.119 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.006 | 0.042 |
| Scholarly communication | 0.022 | 0.077 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.017 | 0.031 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".