diff --git "a/scores.json" "b/scores.json"
--- "a/scores.json"
+++ "b/scores.json"
@@ -4,27 +4,6 @@
   "revision_semantics": "self denotes the Hugging Face snapshot containing this file; the native artifact fingerprint binds its evaluated model files.",
   "score_scale": "0-1; multiply by 100 for percentages",
   "matrix": {
-    "embedding": {
-      "model": "llm-semantic-router/Vela-1.0-Encoder-307M-Embedding",
-      "revision": "972c180aecd2aa3fca97159098ab00d25d53fffb",
-      "artifact_fingerprint_sha256": "2b4747393b1e3e477fb1391a5d6817917362ab68fc5ae2436c769a7357a541ce",
-      "metrics": {
-        "text.banking77.accuracy": {
-          "numerator": 2464,
-          "denominator": 3080,
-          "value": 0.8
-        },
-        "text.massive-en.accuracy": {
-          "numerator": 2248,
-          "denominator": 2972,
-          "value": 0.756393001345895
-        }
-      },
-      "not_applicable": [
-        "image",
-        "audio"
-      ]
-    },
     "small": {
       "model": "llm-semantic-router/multi-modal-embed-small",
       "revision": "fdf8e01b7b0f3a69ac1ac8e2a64dcb1ede177ba4",
@@ -102,159 +81,83 @@
         }
       }
     },
-    "large": {
-      "model": "llm-semantic-router/multi-modal-embed-large",
-      "revision": "e21cde3ccc414c56f504b322662f42c603a939ee",
-      "artifact_fingerprint_sha256": "8439b0c46c36d13a6371081cf7e40cf2c1cc7df68a2bf69e41d514452f65d549",
-      "metrics": {
-        "text.banking77.accuracy": {
-          "numerator": 2334,
-          "denominator": 3080,
-          "value": 0.7577922077922078
-        },
-        "text.massive-en.accuracy": {
-          "numerator": 2149,
-          "denominator": 2972,
-          "value": 0.7230820995962315
-        },
-        "image.image_to_text.recall@1": {
-          "numerator": 350,
-          "denominator": 823,
-          "value": 0.425273390036452
-        },
-        "image.image_to_text.recall@5": {
-          "numerator": 619,
-          "denominator": 823,
-          "value": 0.7521263669501823
-        },
-        "image.image_to_text.recall@10": {
-          "numerator": 721,
-          "denominator": 823,
-          "value": 0.8760631834750912
-        },
-        "image.text_to_image.recall@1": {
-          "numerator": 1442,
-          "denominator": 4115,
-          "value": 0.35042527339003643
-        },
-        "image.text_to_image.recall@5": {
-          "numerator": 2884,
-          "denominator": 4115,
-          "value": 0.7008505467800729
-        },
-        "image.text_to_image.recall@10": {
-          "numerator": 3453,
-          "denominator": 4115,
-          "value": 0.8391251518833536
-        },
-        "audio.audio_to_text.recall@1": {
-          "numerator": 1488,
-          "denominator": 2611,
-          "value": 0.5698965913443125
-        },
-        "audio.audio_to_text.recall@5": {
-          "numerator": 2137,
-          "denominator": 2611,
-          "value": 0.8184603600153199
-        },
-        "audio.audio_to_text.recall@10": {
-          "numerator": 2296,
-          "denominator": 2611,
-          "value": 0.8793565683646113
-        },
-        "audio.text_to_audio.recall@1": {
-          "numerator": 2051,
-          "denominator": 2610,
-          "value": 0.785823754789272
-        },
-        "audio.text_to_audio.recall@5": {
-          "numerator": 2454,
-          "denominator": 2610,
-          "value": 0.9402298850574713
-        },
-        "audio.text_to_audio.recall@10": {
-          "numerator": 2532,
-          "denominator": 2610,
-          "value": 0.9701149425287356
-        }
-      }
-    },
     "candidate": {
       "model": "llm-semantic-router/Vela-1.0-Omni-Nano",
       "revision": "self",
-      "artifact_fingerprint_sha256": "fb9cd39c9980a085b75456c715c2295b997784fe733314be68c13635f6384edf",
+      "artifact_fingerprint_sha256": "96d76f97478e114b816df3ab1b3c6947e4c5ef0babfb40ab865d7e3c838d34c4",
       "metrics": {
         "audio.audio_to_text.recall@1": {
           "denominator": 2611,
-          "numerator": 235,
-          "value": 0.09000382995021065
+          "numerator": 448,
+          "value": 0.17158176943699732
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         "audio.audio_to_text.recall@10": {
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-          "numerator": 822,
-          "value": 0.31482190731520493
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         "audio.audio_to_text.recall@5": {
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-          "value": 0.22290310225967064
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         "audio.text_to_audio.recall@1": {
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-          "numerator": 366,
-          "value": 0.14022988505747128
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         "audio.text_to_audio.recall@10": {
           "denominator": 2610,
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-          "value": 0.4042145593869732
+          "numerator": 1459,
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         "audio.text_to_audio.recall@5": {
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-          "numerator": 827,
-          "value": 0.3168582375478927
+          "numerator": 1204,
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         },
         "image.image_to_text.recall@1": {
           "denominator": 823,
-          "numerator": 540,
-          "value": 0.6561360874848117
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+          "value": 0.6087484811664642
         },
         "image.image_to_text.recall@10": {
           "denominator": 823,
-          "numerator": 791,
-          "value": 0.9611178614823815
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         "image.image_to_text.recall@5": {
           "denominator": 823,
-          "numerator": 731,
-          "value": 0.8882138517618469
+          "numerator": 717,
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         },
         "image.text_to_image.recall@1": {
           "denominator": 4115,
-          "numerator": 2184,
-          "value": 0.5307411907654921
+          "numerator": 2297,
+          "value": 0.5582017010935602
         },
         "image.text_to_image.recall@10": {
           "denominator": 4115,
-          "numerator": 3847,
-          "value": 0.934872417982989
+          "numerator": 3879,
+          "value": 0.9426488456865127
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         "image.text_to_image.recall@5": {
           "denominator": 4115,
-          "numerator": 3465,
-          "value": 0.8420413122721749
+          "numerator": 3507,
+          "value": 0.8522478736330498
         },
         "text.banking77.accuracy": {
           "denominator": 3080,
-          "numerator": 2366,
-          "value": 0.7681818181818182
+          "numerator": 2710,
+          "value": 0.8798701298701299
         },
         "text.massive-en.accuracy": {
           "denominator": 2972,
-          "numerator": 2061,
-          "value": 0.6934724091520862
+          "numerator": 2436,
+          "value": 0.819650067294751
         }
-      }
+      },
+      "parameters": 144554112
     }
   },
   "datasets": {
@@ -312,102 +215,103 @@
     "similarity": "FP32 cosine of L2-normalized embeddings",
     "ties": "lexicographic candidate ID",
     "retrieval": "complete candidate pools; all annotated positives",
-    "classification": "nearest normalized mean class prototype; Vela Omni uses supervised training-split intent-label adaptation; comparison models evaluated as published",
+    "classification": "Nearest normalized mean class prototype from labeled training examples; the original small comparator has task-adapted history, while current GIST is frozen.",
     "aggregation": "Each family is the mean of its two primary metrics; utility is the mean of all six primaries. Retrieval primaries are R@1; R@5 and R@10 are reported separately.",
-    "evaluation_scope": "fixed test-split evaluation pools reused across releases"
+    "evaluation_scope": "fixed test-split evaluation pools reused across releases",
+    "text_training_scope": "Current GIST text tower is frozen; supervised training prototypes are recomputed under the fixed common protocol. The earlier small comparator has task-adapted history. This is not the official MTEB classification protocol."
   },
   "paired_uncertainty": {
     "original": {
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         "text.banking77.accuracy": {
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         "text.massive-en.accuracy": {
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+          "lower": 0.14554621848739496,
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         "utility": {
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-          "upper": 0.12072061135783345
+          "lower": 0.16995251624973068,
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       },
       "method": "paired stratified group percentile; PCG64; fixed candidate pools",
@@ -415,7 +319,7 @@
       "seed": 20260918,
       "comparison": {
         "candidate": "llm-semantic-router/Vela-1.0-Omni-Nano",
-        "candidate_artifact_fingerprint_sha256": "fb9cd39c9980a085b75456c715c2295b997784fe733314be68c13635f6384edf",
+        "candidate_artifact_fingerprint_sha256": "96d76f97478e114b816df3ab1b3c6947e4c5ef0babfb40ab865d7e3c838d34c4",
         "baseline": "llm-semantic-router/multi-modal-embed-small",
         "baseline_revision": "fdf8e01b7b0f3a69ac1ac8e2a64dcb1ede177ba4",
         "baseline_artifact_fingerprint_sha256": "684fe0c48a4ddd3944167f6e5dc75e97ada24e5b120bd9a2921f00dc03112eeb"
@@ -424,94 +328,94 @@
     "previous": {
       "intervals": {
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         "audio.audio_to_text.recall@10": {
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+          "lower": 0.13256556125090607,
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         "text.banking77.accuracy": {
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         "text.massive-en.accuracy": {
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         "utility": {
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       },
       "method": "paired stratified group percentile; PCG64; fixed candidate pools",
@@ -519,70 +423,44 @@
       "seed": 20260918,
       "comparison": {
         "candidate": "llm-semantic-router/Vela-1.0-Omni-Nano",
-        "candidate_artifact_fingerprint_sha256": "fb9cd39c9980a085b75456c715c2295b997784fe733314be68c13635f6384edf",
+        "candidate_artifact_fingerprint_sha256": "96d76f97478e114b816df3ab1b3c6947e4c5ef0babfb40ab865d7e3c838d34c4",
         "baseline": "llm-semantic-router/Vela-1.0-Omni-Nano",
-        "baseline_revision": "70c3412bb0ddfb19386d673d4a102c753a574f1b",
-        "baseline_artifact_fingerprint_sha256": "b596f1dbab89369555e0a72a0d6854d780e305686750949b308c8f167993bdeb"
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   "training_scope": {
-    "text": "Banking77 and MASSIVE English training examples and intent labels; task-adapted classification, not zero-shot transfer or standard MTEB classification",
-    "image": "Image-only alignment using all 16,509 eligible COCO training images, 81,998 canonical training-caption texts and all 82,522 positive image-caption associations; the vision tower is frozen and the image affine projection is optimized. Evaluation examples are excluded.",
-    "audio": "LibriSpeech train-clean-100 speech-transcript subset",
-    "inherited_history": {
-      "text": "Banking77 and MASSIVE English training examples and intent labels; task-adapted classification, not zero-shot transfer or standard MTEB classification",
-      "audio": "LibriSpeech train-clean-100 speech-transcript subset",
-      "previous_image_alignment": "COCO CC-BY2 training image-caption subset",
-      "source_revision": "70c3412bb0ddfb19386d673d4a102c753a574f1b",
-      "source_native_artifact_sha256": "b596f1dbab89369555e0a72a0d6854d780e305686750949b308c8f167993bdeb",
-      "text_and_audio_parameters_unchanged_in_this_update": true
-    }
+    "text": "The complete text tower is the frozen official avsolatorio/GIST-small-Embedding-v0 checkpoint at 75e62fd210b9fde790430e0b2f040b0b00a021b1. Its model card discloses MTEB classification training data; no claim of independent pretraining data is made.",
+    "image": "Frozen current vision encoder and initial image head; an orthogonal shared-space rotation is trained on 16,509 COCO training images, 81,998 unique caption texts and 82,522 complete positive associations, then folded into the image affine head.",
+    "audio": "Frozen current speech encoder and initial audio head; a separate orthogonal shared-space rotation is trained on 28,535 LibriSpeech train-clean-100 clips and all positive transcript associations, then folded into the audio affine head.",
+    "procedure": "One fixed 300-step run; only the final artifact is reported. Encoders remain frozen. The two rotations preserve within-modality inner products, up to floating-point rounding.",
+    "evaluation_scope": "Common text classification uses labeled training prototypes with the earlier task-adapted comparator. It is separate from the official frozen-encoder MTEB classification protocols."
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   "descriptive_metrics": {
     "definition": "Macro-F1 is the unweighted mean of per-class F1 across all fixed prototype classes; zero_division=0.",
     "scope": "Same models, examples, class prototypes and predictions as the accuracy matrix.",
     "metrics": {
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@@ -597,23 +475,20 @@
       "nano": {
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         "revision": "self",
-        "native_artifact_sha256": "fb9cd39c9980a085b75456c715c2295b997784fe733314be68c13635f6384edf",
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-      "embedding_307m": {
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-        "revision": "972c180aecd2aa3fca97159098ab00d25d53fffb",
-        "evaluation_max_text_tokens": 128
+        "max_text_tokens": 32768,
+        "applicability": "NOTICE-only update; computation identical to evaluated native artifact."
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@@ -649,21 +524,20 @@
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@@ -671,36 +545,20 @@
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@@ -721,21 +579,20 @@
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@@ -743,36 +600,20 @@
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@@ -2635,33 +2709,33 @@
       },
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@@ -3220,75 +3294,75 @@
         "split": "test",
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@@ -3301,13 +3375,13 @@
         "split": "valid",
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@@ -3320,18 +3394,18 @@
         "split": "test",
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@@ -3491,6 +3565,105 @@
           "mteb_version": "2.21.0"
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@@ -3502,54 +3675,56 @@
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@@ -3564,79 +3739,65 @@
         "full_MAEB": false,
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   "net_benefit": {
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+        "primary_metric": "cosine_spearman",
+        "task": "STS22.v2",
+        "task_type": "STS"
       }
     ],
-    "tradeoff": "OxfordPets zero-shot accuracy decreases while image linear-probe accuracy, clustering NMI and cross-modal retrieval improve. All task scores and regressions remain reported."
-  }
+    "audio_task_delta_pp": {
+      "BeijingOpera": 0.0,
+      "BirdCLEF": 0.0,
+      "CREMADPairClassification": 0.12104996267769952,
+      "CREMA_D": 0.0,
+      "CREMA_DClustering": 0.0,
+      "CommonLanguageAgeDetection": 0.0,
+      "GTZANAudioReranking": 0.0,
+      "GTZANGenre": 0.0,
+      "IEMOCAPGender": 0.0,
+      "JamAltArtistA2ARetrieval": 0.0,
+      "MInDS14": 0.0,
+      "MridinghamTonic": -0.14336917562723928,
+      "NMSQAPairClassification": -0.1520590751812989,
+      "SIBFLEURS": 0.0,
+      "VehicleSoundClustering": 0.0,
+      "VoxCelebSA": 0.0,
+      "VoxPopuliAccentPairClassification": -0.02844431688273641,
+      "VoxPopuliGenderClustering": 0.0,
+      "VoxPopuliLanguageID": 0.0
+    },
+    "paired_interval_scope": "Paired intervals cover the original common metrics, family and two-primary-per-family utility. They are not confidence intervals for the new all-14 common mean or the four-component product aggregate."
+  },
+  "paired_uncertainty_scope": "Paired intervals cover the original common metrics, family and two-primary-per-family utility. They are not confidence intervals for the new all-14 common mean or the four-component product aggregate."
 }