<tt>pinta</tt>: The uGMRT data processing pipeline for the Indian Pulsar Timing Array
Bibliographic record
Abstract
Abstract We introduce pinta , a pipeline for reducing the upgraded Giant Metre-wave Radio Telescope (uGMRT) raw pulsar timing data, developed for the Indian Pulsar Timing Array experiment. We provide a detailed description of the workflow and usage of pinta , as well as its computational performance and RFI mitigation characteristics. We also discuss a novel and independent determination of the relative time offsets between the different back-end modes of uGMRT and the interpretation of the uGMRT observation frequency settings and their agreement with results obtained from engineering tests. Further, we demonstrate the capability of pinta to generate data products which can produce high-precision TOAs using PSR J1909 $-$ 3744 as an example. These results are crucial for performing precision pulsar timing with the uGMRT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 | 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 teacher head, 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".