Today

Whoop and bundles support

Fix last week

make date filtering work with the FHIR server

date filters

submission

Adds a third custom IntegratedML IRISModel, this one a classifier, and the machinery to work out who is right when it contradicts the published DR3 label.

GaiaVariableType predicts variable-star type from 27 light-curve statistics computed off the per-epoch arrays: amplitude and scatter, skew and kurtosis, the Abbe parameter, a Stetson index, a Lomb-Scargle period and peak power, BP-RP colour, and ESA's own reject rates as features rather than a target. Labels come from gaiadr3.vari_classifier_result, so the ground truth is ESA's published classification. Held-out macro F1 0.938 over nine classes, 0.887 (YSO) to 0.991 (AGN). Registered through pathtoclassifiers, the mirror of the two NGBoost regressors already here, so the repo now exercises both AutoML pools. Run with do ^Classify.

Where the classifier and the catalogue disagree, do ^Adjudicate settles it in three stages of increasing cost, so nothing reaches a language model that arithmetic could have settled. Centroid distance decides 64.3% in the model's favour; k-means collapses about 50 label pairs into 6 recurring degeneracies. Only what survives goes to SIMBAD and an AI Hub agent, which weighs the published literature.

SIMBAD re-publishes Gaia's own variability catalogue, so every object-type query filters bibcode 2022yCat.1358 out. Treating those as independent evidence would mean checking ESA's labels with ESA's labels.

Well-studied stars route to a recursive pass over the bibliography (rlm-core) instead of truncating it to a keyword-ranked top 20. Also adds three test suites, including a cold-start regression that restarts the container before asserting PREDICT() returns rows.

The ObjectScript edition now processes the 20 independent Gaia DR3 input files in parallel using IRIS %SYSTEM.WorkMgr.

Each input file is processed as an independent work unit. The parent routine merges worker results in deterministic file and row order, preserving byte-identical output with the previously verified serial implementation.

The updated edition continues to produce 57,099 qualifying sources, passes all 16 validation cases, and matches the independent Python reference oracle.

In local testing, the median internal processing time improved from approximately 101 seconds for the serial implementation to approximately 33.6 seconds for the parallel implementation. Official moderator results may differ.

Similar to previous code but with unzip and warm start optimizations if allowed

added fhir server settings

udapte with WebApplication

add json support

add streams support for messages content

extra payload data

Added fix for handling possible stale .so file from previous builds

Initial Release

Initial Release

Initial Release

Separated gzip decompression from actual file processing, as realized the timed portion of RunScript for the benchmark, does need to include this step, implemented and added it as a pre-step

1. Improved performance -
   1. Using local container storage
   2. Using all cores
2. Shortened "short profile"
   1. Removed output file header line
   2. Changed some conditions

Initial Release

Reduced to 313 symbols

0.08s

Initial Release

Initial Release

added submenu

fix refresh

added adapters support

Apply production changes

production changes