metadata: add score_type/score_params/score_protocol (official grading protocol taxonomy); task_type is now format-only (judge_scored migrated to vqa + llm_judge). See dataset-upload skill references/metadata-json.md.

metadata.json

@@ -10,6 +10,11 @@
         "single_video_start"
       ],
       "task_type": "multiple_choice_vqa",
+      "score_type": "rule",
+      "score_protocol": {
+        "reference": "lmms-eval@lmms_eval/tasks/vsibench/utils.py:87-89,115-121 — MCA question types graded by fuzzy_matching (first token, strip trailing period) + case-insensitive exact match against the ground-truth letter; no LLM.",
+        "note": "The org ships ONLY the multiple-choice question types (mc config, 2490 rows; confirmed in rows file). The official benchmark also contains NA (numerical) types graded with Mean Relative Accuracy MRA:.5:.95:.05 (utils.py:95-100,29-31), and the official headline 'overall' averages 8 per-question-type scores after averaging object_rel_direction easy/medium/hard (utils.py:158-170) — neither is reproducible from this copy or from a per-sample mean. Rows carry extra 'question_type' with VSI type names (object_rel_direction_hard, ...) that are not scorer vocabulary."
+      },
       "prompt_template": "<video>These are frames of a video.\n{{ question }}\nOptions:\n{% for o in options %}{{ o }}\n{% endfor %}Answer with the option's letter from the given choices directly.",
       "prompt_template_source": {
         "origin": "official",