Additional file 1 of Genomic approaches to trace the history of human brain evolution with an emerging opportunity for transposon profiling of ancient humans
Bibliographic record
Abstract
Additional file 1: previous_studies_with_ancient_data.xlsx. Table S1. Genome-wide aDNA data in addition to those curated in Marciniak and Perry Nat Rev Genet 2017. Table S2. Summary of genome-wide aDNA studies by year of publication and geographic region. The authors apologize for any accidental omissions of published ancient human or archaic hominin genomic data sets. These data are otherwise intended to be current as of December 2020. SNP, single-nucleotide polymorphism; WGS, whole-genome sequencing. * > 1× indicates an average coverage greater than 1-fold. ** > 5× indicates an average coverage greater than 5-fold. ‡Geographic region definitions: - Central Europe: Croatia, the Czech Republic, Hungary, Austria, Poland, Germany, Switzerland, Serbia, Slovakia. - Eastern Europe: Belarus, the Ukraine, Russia, Bulgaria, Montenegro, Caucasus, Romania, Moldova, Armenia. - Northern Europe: Estonia, Denmark, Sweden, Lithuania, Latvia, Ireland, United Kingdom, Norway, Netherlands, Belgium, France, Luxembourg, Finland, Iceland, Isle of Man. - Southern Europe: Spain, Portugal, Italy, Greece, Macedonia. - Asia: Nepal, China, India, Pakistan, Mongolia, Thailand, Cambodia, Vietnam, Laos, Malaysia, Indonesia, Philippines, Japan, Kazakhstan, Uzbekistan, Tajikistan, Turkmenistan, Afghanistan, Kyrgyzstan. - Middle East: Iran, Israel, Turkey, Jordan, Lebanon, Yemen. - North America: Canada, United States, Greenland, Central America, the Caribbean, Mexico, Bahamas, − South America: Brazil, Chile, Bolivia, Peru, Argentina, Venezuela. - Africa: Ethiopia, Egypt, Chad, Nigeria, Morocco. - Oceania: Vanuatu, Australia, Tonga, Solomon Islands, French Polynesia. §For subsets of samples without reported specific dates.
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.
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 | 0.002 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.865 | 0.161 |
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".