Sequencing and Analyzing the Transcriptomes of a Thousand Species Across the Tree of Life for Green Plants
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 1,000 Plants (1KP) initiative was the first large-scale effort to collect next-generation sequencing (NGS) data across a phylogenetically representative sampling of species for a major clade of life, in this case the Viridiplantae , or green plants. As an international multidisciplinary consortium, we focused on plant evolution and its practical implications. Among the major outcomes were the inference of a reference species tree for green plants by phylotranscriptomic analysis of low-copy genes, a survey of paleopolyploidy (whole-genome duplications) across the Viridiplantae , the inferred evolutionary histories for many gene families and biological processes, the discovery of novel light-sensitive proteins for optogenetic studies in mammalian neuroscience, and elucidation of the genetic network for a complex trait (C 4 photosynthesis). Altogether, 1KP demonstrated how value can be extracted from a phylodiverse sequencing data set, providing a template for future projects that aim to generate even more data, including complete de novo genomes, across the tree of life.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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