NEAR-INFRARED (<i>JHK</i>) SPECTROSCOPY OF YOUNG STELLAR AND SUBSTELLAR OBJECTS IN ORION
Bibliographic record
Abstract
We performed low-resolution ( R ∼ 40) near-infrared (0.9–2.4 μm) multi-object spectroscopy of 240 isolated point sources having apparent H -band magnitudes between 9 and 18 in the central 5' × 6' of the Orion Trapezium cluster. The observations were performed over four nights at the Canada–France–Hawaii Telescope using the visiting instrument SIMON, an infrared imager and multi-object spectrograph. We present the spectra of 104 objects with accurately derived spectral types including 7 new objects having masses below the hydrogen-burning limit, and 6 objects with masses below the deuterium-burning limit. The spectral classification is performed by fitting previously classified spectral templates of dwarf stars (K4–M3) and optically classified young stellar and substellar objects (M4–L0), to the entire 0.9–2.4 μm spectral energy distribution in order to assign a spectral type and visual extinction for each object. Of the 104 objects studied, 44 have been previously classified spectroscopically using various techniques. We perform a rigorous comparison between the previous classifications and our own and find them to be in good agreement. Using the dereddened H -band magnitudes, the classified objects are used to create an Hertzsprung–Russell diagram for the cluster. We find that the previous age estimates of ∼1 Myr to be consistent with our results. Consistent with previous studies, numerous objects are observed to have luminosities several magnitudes above the 1 Myr isochrone. Numerous objects exhibiting emission features in the J band are also reported.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".