Knowing the Biosphere: Documentation, Specimens, Archives, and Names Reveal Environmental Change and Emerging Pathogens
Bibliographic record
Abstract
One Health programs and trajectories are now the apparent standard for exploring the occurrence and distribution of emerging pathogens and disease. By definition, One Health has been characterized as a broadly inclusive, collaborative, and transdisciplinary approach with connectivity across local to global scales, which integrates the medical and veterinary community to recognize health outcomes emerging at the environmental nexus for people, animals, plants, and their shared landscapes. One Health has been an incomplete model, conceptually and operationally, focused on reactive and response-based foundations, to limit the impact of emerging pathogens and emerging infectious diseases and, as such, lacks a powerful proactive capacity. A proactive, predictive One Health is necessary, emanating in part from geographically/taxonomically broad and temporally deep biological collections of pathogen-host assemblages. The DAMA protocol (Document, Assess, Monitor, Act), the operational extension of the Stockholm paradigm (SP), accomplishes this task by encompassing holistic and strategic biological sampling of reservoir host assemblages and pathogens at environmental interfaces and more extensively through resurveys, with development of informatics resources digitally linked to physical specimens held in publicly accessible museum biorepositories. Archives of specimens are the foundations for accumulating interrelated archives of information (the baselines against which change can be identified and tracked), with collections serving as fundamental resources for biodiversity informatics under the conceptual evolutionary and ecological umbrella of the SP. A cultural and conceptual transformation is essential among the diverse practitioners in the One Health community, one that recognizes the necessity of placing pathogens in an evolutionary, ecological, and environmental context by integrating specimens and associated informatics into an infrastructure and networks for actionable information. As a community, it is essential to abandon response-based business as usual while looking forward toward proactive transboundary approaches that maximize our conceptual and taxonomic view of diversity across interconnected planetary scales that influence the complexity of pathogen-host interfaces. Evolution, where the past always influences the present and the future, defines our trajectory, as the need for sustained archives that describe the biosphere becomes more acute with each passing day.
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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 | 0.070 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".