research: preregister AttnRes spike path study
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{
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"schema_version": 1,
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"protocol_id": "llm-atlas-k3-attnres-spike-path-v1",
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"parent_protocol_id": "llm-atlas-k3-attnres-gradient-scale-v1",
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"study_identity": "targeted follow-up informed by Round 05; not blind discovery",
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"architecture": "block",
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"depth": 32,
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"aggregation_groups": 8,
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"formal_seeds": [
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2026073001,
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2026073002,
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2026073003
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],
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"replay": {
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"architecture": "block",
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"depth": 32,
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"seed": 2026073001
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},
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"training": {
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"steps": 8000,
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"batch_size": 32,
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"context": 256,
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"target_bytes_per_cell": 65536000,
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"diagnostic_steps": [
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0,
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100,
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500,
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2000,
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4000,
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8000
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]
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},
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"positions": [
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"pre_attention_input",
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"attention_branch_output",
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"post_attention_state",
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"pre_mlp_input",
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"mlp_branch_output",
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"post_mlp_state"
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],
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"reductions": {
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"confirmatory": [
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"element_rms",
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"token_rms_mean",
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"token_rms_median",
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"token_rms_p95"
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],
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"exploratory": [
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"batch_mean_rms",
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"token_mean_rms"
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],
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"algebraic_control": [
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"global_l2"
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],
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"quantile_definition": "Hyndman-Fan Type 7 linear interpolation on explicitly sorted values"
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},
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"interventions": {
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"modes": [
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"learned",
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"detached_learned",
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"uniform_value_backward"
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],
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"steps": [
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0,
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8000
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],
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"scope": "all 64 depth mixers plus the output mixer",
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"training_uses_custom_autograd": false,
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"confirmatory_reduction": "element_rms"
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},
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"spike_layers_one_based": [
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21,
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22,
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23,
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24,
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25
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],
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"thresholds": {
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"spike_contrast": 1.5,
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"top_five_min_overlap": 3,
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"spearman_minimum": 0.8,
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"material_relative_drop": 0.2,
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"spectrum_absolute_tolerance": 1e-06,
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"raw_relative_tolerance": 1e-06,
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"positive_denominator_epsilon": 1e-30
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},
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"parent_artifacts": {
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"manifest_path": "experiments/k3/attnres_gradient/manifest.json",
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"manifest_sha256": "080afb17d1e036c0bba0a799fdb8b98ee4ad652bd42dd1b3b67110dd2ede6371",
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"runner_path": "experiments/k3/attnres_gradient/train.py",
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"runner_sha256": "04ae69e10c58972c9193c2d31c7e09d924a0d0e834107afa4ba128c64ac5800f",
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"protocol_path": "research/K3_ATTNRES_GRADIENT_SCALE_PROTOCOL.md",
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"protocol_sha256": "f772629b3b82975b6756721c3a3bb57cc4171dfa26ba5b1e8043dc91c9dcce22",
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"formal_schedule_sha256": "5041e09b167f229248d2462324e8c254b8f5938975f135dcd8192b00a54a4f4e",
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"validation_tensor_sha256": "f459316f13078a163b47c133511bb7181e05170ab89516e196490113893ce338",
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"diagnostic_tensor_sha256": "21117e31db302b10d67b63f035665dc8f220b879d216ccd12b7d2ba86e7b1716"
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},
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"round05_expected": {
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"2026073001": {
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"raw_file_sha256": "29e1d638b481619c7b32de402122523db8b17cc1fc67a8881fa1ba132a1d5c38",
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"canonical_sha256": "c7554d9beea6fe9e63617aafd88403f7fc93b4b305a0c6d603a98a8572e5b5f1",
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"final_model_state": "3f0b97ece3a15571ba3d656f589f512ca0bb9e20083c9f58a42ccaee14892f59",
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"final_optimizer_state": "ed03e6fbd4a12d8b063dcb22e0437754285f54d585374cd52fbd534f05d24637"
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},
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"2026073002": {
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"raw_file_sha256": "21199deb2199395061e51220fd8c7afd04a1135a6381e406da9b5795e3ad5032",
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"canonical_sha256": "b4262e697e2269457fdebf31f75008383c6e8024ee1bbf96e5962fb2ba1dec18",
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"final_model_state": "bd2556388aeaa211b798c283c7cbd8ccd29edf166a2922fa13d172e8dfdc38d1",
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"final_optimizer_state": "0b101eab3bc7d8d654be2ea335c86fc25563ce19912d721844ee4e639c569e77"
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},
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"2026073003": {
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"raw_file_sha256": "c0d7f1bcfa9fa7f8f3134ca4571bdf23a951182d03b7de9611a6b4b89667d4ac",
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"canonical_sha256": "513b85666fcdbf75424596e968cd73733314ec188345e453998de08b18dcef65",
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"final_model_state": "638568aede21890773b6932a19ec4e112f5ac0a4770ba3402fcd82980a9ecf76",
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"final_optimizer_state": "83947fd743ec8e3e31ca7788fd201981846f0f1c7e9e38c88afcef95cfc6ec4e"
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}
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}
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}
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