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[jturtle]

Hi Lucie,
Thanks for the explanation about parsing the constant-trajectory warnings. While looking into this, I found that we could improve our order of operations. This new submission is qualitatively the same, but reduces the number of numeric artifacts. There are still a hand full of constant trajectories for each of DC and WY, 0-64 mortality, but I have verified that these are non-constant and reasonable before rounding.

Thanks,
Jamie

[github-actions]

Model Output

--- PSI-PROF/2025-04-27-PSI-PROF.gz.parquet ---

✅: [file_exists]: File exists at path 'model-output/PSI-PROF/2025-04-27-PSI-PROF.gz.parquet'.

✅: [file_name]: File name "2025-04-27-PSI-PROF.gz.parquet" is valid.

✅: [file_location]: File directory name matches model_id
metadata in file name.

✅: [round_id_valid]: round_id is valid.

✅: [file_format]: File is accepted hub format.

✅: [file_n]: Number of accepted model output files per round met.

✅: [metadata_exists]: Metadata file exists at path 'model-metadata/PSI-PROF.yaml'.

---

Run validation on files: 2025-04-27-PSI-PROF.gz.parquet

ℹ: [pairing_info]: Run grouping pairing: scenario_id, age_group, horizon, target; stochastic run pairing: scenario_id, age_group, horizon, target. Number of Samples: 300
✅: [valid_round_id_col]: round_id_col name is valid.

✅: [unique_round_id]: round_id column "origin_date" contains a single, unique round ID value.

✅: [match_round_id]: All round_id_col "origin_date" values match submission round_id from file name.

✅: [colnames]: Column names are consistent with expected round task IDs and std column names.

✅: [col_types]: Column data types match hub schema.

✅: [valid_vals]: tbl contains valid values/value combinations.

✅: [rows_unique]: All combinations of task ID column/output_type/output_type_id values are unique.

✅: [req_vals]: Task ID/output type/output_type_id combinations all present.

✅: [value_col_valid]: Values in column value all valid with respect to modeling task config.

ℹ: [value_col_non_desc]: No quantile or cdf output types to check for non-descending values.
Check skipped.
✅: [spl_compound_taskid_set]: All samples in a model task conform to single, unique compound task ID set that matches or is
coarser than the configured compound_taksid_set.
Pairing information: scenario_id, age_group, horizon, target
✅: [spl_compound_tid]: Each sample compound task ID contains single, unique value.

ℹ: [spl_non_compound_tid]: Task ID combinations of non compound task id values not tested
✅: [spl_n]: Required unique number of samples per compound idx task present.
Only one number of samples from: 100 to 300 are accepted. Submission contains: 300
✅: [n_decimal]: value associated with sample is in a valid format.
A maximum of 1 decimal place is expected.
✅: [na_value]: value does not contain NA value.

❗: [flat_projection]: Some projections have a unique value for the whole projection period.
Please verify, for example: E-2025-04-01, 0-64, 11, 2025-04-27, inc death, sample, 7217; B-2025-04-01, 0-64, 11, 2025-04-27, inc death, sample, 7256; E-2025-04-01, 0-64, 11, 2025-04-27, inc death, sample, 7256; A-2025-04-01, 0-64, 56, 2025-04-27, inc death, sample, 5867; B-2025-04-01, 0-64, 56, 2025-04-27, inc death, sample, 5867
✅: [cumul_proj]: The cumulative values are not decreasing.

[LucieContamin]

Hi @jturtle ,

Thank you very much for the update and the information! It seems to be all good, I will merge it!

Best, Lucie