Bibliographic record
Abstract
Our goal is to provide a quantification of several spectral classification criteria for O stars. We collect high-spectral resolution spectra of 105 Galactic O-type stars from various archives. We measured equivalent widths of classification lines. We defined average values of classification criteria for given spectral types and luminosity classes. We find that the ratio He I 4471 to He II 4542 well matches the published ratios for spectral types. We have quantified equivalent width ratios of helium and silicon lines among O8–O9.7 stars to refine spectral class typing in this spectral range. We present quantitative criteria to separate between luminosity class V, IV–III–II (grouped), and I among O3–O8.5 stars, mainly based on the strength of He II 4686. We find that these criteria also define very well the f, (f), and ((f)) classes for O3–O7.5 stars. Among O9–O9.7 stars we quantify the ratios of He II 4686 to He I 4713 and Si IV 4089 to He I 4026 for all luminosity classes. The tabulated values of the classification criteria should help classify any new O-type stars. The final step of the classification process should rely on a direct comparison to standard stars of the assigned spectral type or luminosity class.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".