Interstellar anatomy of the TeV gamma-ray peak in the IC443 supernova remnant
Bibliographic record
Abstract
Supernovae remnants (SNRs) represent a major feedback source from stars on the interstellar medium of galaxies. During the latest stage of supernovae explosions, shock waves produced by the initial blast modify the chemistry of gas and dust, inject kinetic energy in the surroundings, and may alter star formation characteristics. Simultaneously, gamma-ray emission is generated by the interaction between the ambiant medium and the cosmic rays. We study the stellar and interstellar contents of IC443, an evolved shell type SNR at a distance of 1.9 kpc, with an estimated age of 30 kyr. We aim to measure the mass of the gas within the extended G region, which corresponds to the peak of gamma-ray emission detected by VERITAS and Fermi. We performed 10'x10' mapped observations of 12CO and 13CO J=1-0, J=2-1 and J=3-2 pure rotational lines, as well as C18O J=1-0 and J=2-1 obtained with the IRAM-30m and APEX telescopes. We first compared our data with local thermodynamic equilbrium (LTE) models. We estimated the optical depth of each line from the emission of the isotopologues 13CO and C18O. We used the population diagram and large velocity gradient (LVG) assumption to measure the column density, mass, and kinetic temperature of the gas using 12CO and 13CO lines. We used complementary data (stars, gas, and dust at multiple wavelengths) and infrared point source catalogues to search for protostar candidates. Our results emphasize how the mass associated with the ring-like structure and the cloudlet cannot be overlooked when quantifying the interaction of cosmic rays with the dense local medium. Additionally, the presence of numerous possible protostars in the region might represent a fresh source of CR, which must also be taken into account in the interpretation of gamma-ray observations in this region.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".