2003b) Reconciling actual and inferred population histories in the house finch (Carpodacus mexicanus) by AFLP analysis
Bibliographic record
Abstract
Abstract. The house finch (Carpodacus mexicanus) is a native songbird of western North America that was introduced to the eastern United States and Hawaiian Islands in historic times. As such, it provides an unusually good opportunity to test the ability of molecular markers to recover recent details of a known population history. To investigate this prospect, genetic variation in 172 individuals from 16 populations in the western and eastern United States, southeastern Canada, Hawaiian Islands, and Mexico, as well as genetic variation in the closely related purple finch (Carpodacus purpureus) and Cassin’s finch (Carpodacus cassinii) was studied by a semi-automated fluorescence-labeled amplified fragment length polymorphism (AFLP) marker system. A total of 363 markers were generated, of which 258 (71.2%) were polymorphic among species, 166 (61.4%) polymorphic among house finch subspecies, and 157 (60.2%) polymorphic among populations within the frontalis subspecies complex. Heterozygosities and interpopulation divergences revealed by the analysis appeared relatively low at all taxonomic levels, but there are few similar studies in avian populations with which to compare results. Whereas the known population history predicts that both eastern and Hawaiian finches should have been derived from within western populations, tree analysis using both populations and individuals as units suggests weak monophyly of eastern populations and indicates that Hawaiian populations are not clearly derived from California populations. However, the genetic distinctiveness of native and recently founded populations was disclosed by analyses of molecular variance as well as by a model-based assignment approach in
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".