Les datations moléculaires à l’heure de la génomique
Bibliographic record
Abstract
The comparison of DNA and protein sequences of extant species might be informative for reconstructing the chronology of evolutionary events on Earth. A phylogenetic tree inferred from molecular data directly depicts the evolutionary affinities of species and indirectly allows estimating the age of their origin and diversification. Molecular dating is achieved by assuming the molecular clock hypothesis, i.e., that the rate of change of nucleotide and amino acid sequences is on average constant over geological time. If paleontological calibrations are available, then absolute divergence times of species can be estimated. However, three major difficulties potentially hamper molecular dating : (1) a limited sample of genes and organisms, (2) a limited number of fossil references, and (3) pervasive variations of molecular evolutionary rates among genomes and species. To circumvent these problems, different solutions have been recently proposed. Larger data sets are built with more genes and more species sampled through the mining of an increasing number of genomes. Moreover, independent key fossils are identified to calibrate molecular clocks, and the uncertainty on their age is integrated in subsequent analyses. Finally, models of molecular rate variations are constructed, and incorporated in the so-called relaxed molecular clock approaches. As an illustration of these improvements, we mention that the debated age of the animal (bilaterian metazoans) diversification may have occurred between 642-761 million years ago (Mya), roughly 100 Ma before the Cambrian explosion. Among mammals, the initial diversification of major placental groups may have taken place around 100 Mya, well before the Cretaceous/Tertiary boundary marking the extinction of dinosaurs.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".