New Methanol Maser Transitions and Maser Variability Identified from an Accretion Burst Source G358.93-0.03
Bibliographic record
Abstract
Abstract The high-mass young stellar object G358.93-0.03 underwent an accretion burst during the period from 2019 January to June. Given its extraordinary conditions, a number of new maser transitions may have been naturally excited during the burst stage. Searching for new maser lines and monitoring maser variability associated with the accretion burst event are important for understanding the complex conditions of the massive star formation toward G358.93-0.03. In this work, using the Shanghai 65 m Tianma Radio Telescope, we continuously monitored the multiple maser (including methanol and water) transitions toward G358.93-0.03 during the burst in the period from 2019 March 14 to May 20. There were 23 CH3OH maser transitions and one H2O maser transition detected from the monitoring. Nearly all the detected maser transitions toward this source have dramatic variations in their intensities within a short period of ∼2 months. Eight new methanol transitions from G358.93-0.03 were identified to be masering in our observations based on their spectral profile, line width, intensity, and the rotation diagram. During the monitoring, the gas temperature of the clouds in the case of saturated masers can show a significant decline, indicating that the maser clouds were going through a cooling process, possibly associated with the propagation of a heat wave induced by the accretion burst. Some of the maser transitions were even detected with the second flares in 2019 April, which may be associated with the process of the heat-wave propagation induced by the same accretion burst acting on different maser positions.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".