Bibliographic record
Abstract
This Dataset contains the Gemini South/IGRINS spectra of the T6 dwarf 2MASS J08173001-6155158, and two Sonora Bobcat Alternative A models, as presented in Tannock et al. 2022a (submitted to MNRAS January 2022). <br><br> All files are text files. Header information is marked with a '#' at the start of the line. <br><br> There is one file for each IGRINS order in the H and K bands (see Table 2 in Tannock et al. 2022a for the wavelength coverage of each order), as well as an order-stitched file for each of the H and K bands. The data contained in each order is normalized to unity, and the stitched files are normalized to peak at unity. <br><br> The IGRINS data files have four columns:<br> column 1: vacuum wavelength in microns<br> column 2: flux in normalized F_lambda units<br> column 3: uncertainty on the flux<br> column 4: signal-to-noise ratio<br> <br><br> The spectra are telluric corrected (we have divided the science spectrum by the spectrum of an A0V star), and are a weighted average of three epochs. These spectra DO NOT include the quadratic correction for instrument systematics described in Tannock et al. 2022. <br><br><br> The models are Sonora Bobcat Alternative A models generated by Callie Hood (Hood et al. in prep). These models are an alternative version of the Sonora Bobcat models (Marley et al. 2021) with updated molecular line lists (see Table 4 in Tannock et al. 2022a). <br><br> The models have two columns:<br> column 1: vacuum wavelength in microns<br> column 2: flux in F_lambda units (W/m2/m) <br><br> These models have NOT been smoothed for rotation, shifted for RV, resampled to the IGRINS wavelengths, or otherwise altered.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.064 |
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".