Nurturing a sustainable Open Tree of Life
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Open Tree of Life project is a collaborative effort to synthesize, share and update a comprehensive tree of life Fig. 1. We have completed a draft synthesis of a tree summarizing digitally available taxonomic and phylogenetic knowledge for all 2.6 million named species, available at tree.opentreeoflife.org Hinchliff et al. 2015. . . This tree provides ready access to phylogenetic information which can link together biodiversity data on the basis of what we know about relevant evolutionary history. Both the unified reference taxonomy Rees and Cranston 2017 and the published phylogenetic statements underlying the tree McTavish et al. 2015 are available and accessible online. Taxa in the phylogenies are mapped to the the reference taxonomy, which aligns Open Tree taxon identifiers to those from NCBI and GBIF, among several other taxonomy resources. The synthesis tree is revised as new data become available, and captures conflict and consensus across different published phylogenetic estimates. This undertaking requires both development of novel infrastructure and analysis tools, as well as community engagement with the Open Tree of Life project. I will discuss the challenges in and the progress towards achieving these goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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 it