A new synthetic model for asymptotic giant branch stars
Bibliographic record
Abstract
We present a synthetic model for thermally pulsing asymptotic giant branch (TPAGB) evolution constructed by fitting expressions to full evolutionary models in the metallicity range 0.0001 ≤Z≤ 0.02. Our model includes parametrizations of third dredge-up and hot-bottom burning with mass and metallicity. The Large Magellanic Cloud and Small Magellanic Cloud carbon star luminosity functions are used to calibrate third dredge-up. We calculate yields appropriate for galactic chemical evolution models for 1H, 4He, 12C, 13C, 14N, 15N, 16O and 17O. The initial–final mass relation is examined for our stars and found to fit to within 0.1 M⊙ of the observations. We also reproduce well the white dwarf mass function for masses above about 0.58 M⊙. The new model is to be implemented in a rapid binary star evolution code.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".