Molecular evidence for introgressive hybridization in New Zealand masked gulls
Bibliographic record
Abstract
Genetic data and codes to reproduce the analyses from the manuscript : Given, A. D., Mills, J. A., Momigliano, P., & Baker, A. J. (2022). Molecular evidence for introgressive hybridization in New Zealand masked gulls. Ibis. https://doi.org/10.1111/ibi.13117 The data and codes are in two zipped folders FSC.zip PopGen.zip The FSC.zip folder contains data and scripts to reproduce the fastsimcoal simulations and to calculate summary statistics from observed and simulated data. It also includes the results from these analyses and an R script to run ABC model selection via random forest. The PopGen.zip folder contains the microsatellite dataset in both genepop (RB-BB.gen) and structure (RB-BB.str) formats , the results from STRUCTURE analyses (folder RB-BB_STRUCT), and an R script (Popgen_analyses.r) to reproduce population genetic analyses (PCA and summary statistics: FST, and estimate HWE, HO and HE) and plots.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".