Publish the trained metadata-only router checkpoint with its fitted feature builders, verified label map, and a runnable example
0181745 verified | { | |
| "label_order": [ | |
| "baseline_llm", | |
| "single_agent", | |
| "per", | |
| "broadcast", | |
| "none" | |
| ], | |
| "index_to_label": { | |
| "0": "baseline_llm", | |
| "1": "single_agent", | |
| "2": "per", | |
| "3": "broadcast", | |
| "4": "none" | |
| }, | |
| "label_to_index": { | |
| "baseline_llm": 0, | |
| "single_agent": 1, | |
| "per": 2, | |
| "broadcast": 3, | |
| "none": 4 | |
| }, | |
| "note": "The estimator stores integer classes [0..4] with no embedded label map. This file IS that map. It is the paper's fixed cost order, NOT alphabetical order: decoding with sorted(labels) agrees with the released predictions on only 352 of 423 test rows, while this mapping agrees on 423 of 423.", | |
| "verified": { | |
| "check": "model.predict on reconstructed test features, decoded with index_to_label, compared to test_predictions.csv", | |
| "n_test": 423, | |
| "agreement_label_order": "423/423", | |
| "agreement_sorted_order": "352/423" | |
| } | |
| } |