Result-Review-O4a.md

@@ -109,9 +109,9 @@ ML Models:
 
 | File(s) | Short description | Status | Comment | Git hash | Sign-off |
 |---------|-------------------|--------|---------|----------|----------|
-| [pop_datasets.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/pop_datasets.ipynb) | Notebook having plots of injection parameters for training and testing. |  | -------------- |  |  |
-| [PSD_plots.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/PSD_plots.ipynb) | Comparison of the PSDs used for training and testing in O3 and O4 etc. | Done | OK, OK - Sourabh | 5f525a652d0374f11a207bc8158f7c75d37de884 | :heavy_check_mark: :heavy_check_mark: |
-| ML QTs [L1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/L1/uniform_config_lr_0.01_ep_15_bs_500/), [H1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/uniform_config_lr_0.01_ep_15_bs_500/) | Production ML QTs models train directories. Uniform in masses for H1 and L1 |  |  | -------------- |  |
+| [pop_datasets.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/pop_datasets.ipynb) | Notebook having plots of injection parameters for training and testing. | Done  | -------------- |  |  |
+| [PSD_plots.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/PSD_plots.ipynb) | Comparison of the PSDs used for training and testing in O3 and O4 etc. | Reviewed | OK, OK - Sourabh | 5f525a652d0374f11a207bc8158f7c75d37de884 | :heavy_check_mark: :heavy_check_mark: |
+| ML QTs [L1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/L1/uniform_config_lr_0.01_ep_15_bs_500/), [H1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/uniform_config_lr_0.01_ep_15_bs_500/) | Production ML QTs models train directories. Uniform in masses for H1 and L1 | Done |  | -------------- |  |
 | [2vs3det.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/2vs3det.ipynb) | Train and Test ML Skymaps. Benchmark performance for HL v/s HLV | OK | Why some values are NaN in DataFrame?, Why no orange curve in plots?, Choice of hyperparameters for training? - Sourabh | 5f525a652d0374f11a207bc8158f7c75d37de884 | :heavy_check_mark: |
 | [make_predictions.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/make_predictions.ipynb?ref_type=heads) |Demo LensID O4a, ML models benchmark performance and background estimations. | Need to clean up |  | -------------- |  |
 
@@ -122,7 +122,7 @@ O4a Predictions:
 | File(s) | Short description | Status | Comment | Git hash | Sign-off |
 |---------|-------------------|--------|---------|----------|----------|
 | [Config](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/config_o4a.yaml?ref_type=heads) | ML models and config for production runs |  Done|  | -------------- |  |
-| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT |  |  | -------------- |  |
+| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT | Done  |  | -------------- |  |
 | [investigations_visualisations.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/investigations_visualisations.ipynb?ref_type=heads) | ML pipeline run through a notebook with Investigations/Eyeballing pairs and comparing the performances with the other pipelines | Done |  | -------------- |  |
 
 Publication results: