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Merged
AlexanderFengler merged 2 commits into from
Aug 28, 2026
Merged

Archive the fixed PSDM recovery preregistration #1214

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9d2539c
benchmark: predeclare fixed PSDM recovery scenarios
AlexanderFengler Aug 17, 2026
a9ca609
test: bind archived PSDM preregistration
AlexanderFengler Aug 28, 2026
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330 changes: 330 additions & 0 deletions benchmarks/specs/jeam_fixed_psdm_recovery_v1.json
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{
"schema_version": 1,
"study_id": "jeam-fixed-psdm-recovery-v1",
"status": "preregistered-before-canonical-run",
"frozen_at_utc": "2026-08-17T04:04:00Z",
"question": "Does the fixed projected-spherical JEAM likelihood preserve its optimizer inside HSSM and support converged ordered-Slice recovery with calibrated polar predictive summaries?",
"canonical_results_must_postdate_this_file_commit": true,
"scope": {
"model": "projected_spherical_diffusion",
"response_columns": [
"rt",
"response"
],
"response_contract": {
"rt": "finite and strictly positive",
"response": "finite polar angle in the closed interval [0, pi]"
},
"density_measure": "d(rt) d(response)",
"parameter_order": [
"v_x",
"v_y",
"a",
"t"
],
"parameter_meaning": {
"v_x": "axial drift",
"v_y": "nonnegative projected-radial drift",
"a": "fixed threshold",
"t": "nondecision time"
},
"fixed_model_settings": {
"sigma": 1.0,
"s_v": 0.0,
"s_t": 0.0,
"threshold_dynamic": "fixed",
"decay": 0.0,
"threshold_function": null,
"p_outlier": null
}
},
"provenance": {
"hssm_stack_base_revision": "11fdc2236711f46d3bd6ba19589947fc20285ff1",
"jeam_revision": "1d7112757d8b2d27a31437255fc679194d39ab89",
"python_minor": "3.12",
"pytensor_floatx": "float64",
"environment": "HSSM pyproject optional JEAM source pinned to the recorded immutable revision",
"required_result_metadata": [
"hssm_revision",
"jeam_revision",
"pyproject_sha256",
"python_version",
"package_versions",
"platform",
"processor",
"logical_cpu_count"
]
},
"priors_and_initialization": {
"policy": "Construct the ordinary built-in HSSM model with its public defaults, assert the resolved priors and initvals equal this specification, and pass the same initvals to every ordered-Slice fit without jitter.",
"priors": {
"v_x": {
"distribution": "Uniform",
"lower": -3.0,
"upper": 3.0
},
"v_y": {
"distribution": "Uniform",
"lower": 0.0,
"upper": 3.0
},
"a": {
"distribution": "Uniform",
"lower": 0.1,
"upper": 3.0
},
"t": {
"distribution": "HalfNormal",
"sigma": 2.0
}
},
"configured_bounds": {
"v_x": [
-3.0,
3.0
],
"v_y": [
0.0,
3.0
],
"a": [
0.1,
3.0
],
"t": [
0.0,
2.0
]
},
"resolved_untransformed_initvals": {
"v_x": 0.0,
"v_y": 1.5,
"a": 1.5,
"t": 0.025
}
},
"scenarios": [
{
"name": "baseline_asymmetric",
"truth": [
0.6,
1.0,
1.1,
0.2
],
"trials": 400,
"data_seed": 1592,
"optimizer_seed": 8695309,
"chain_seeds": [
7101,
7102,
7103,
7104
],
"prior_predictive_seed": 11101,
"posterior_predictive_seed": 11291
},
{
"name": "reverse_axial_weak_radial",
"truth": [
-0.7,
0.45,
0.85,
0.1
],
"trials": 400,
"data_seed": 2703,
"optimizer_seed": 54221,
"chain_seeds": [
8201,
8202,
8203,
8204
],
"prior_predictive_seed": 12101,
"posterior_predictive_seed": 12291
},
{
"name": "high_threshold_strong_radial",
"truth": [
0.3,
1.25,
1.5,
0.22
],
"trials": 400,
"data_seed": 3814,
"optimizer_seed": 64231,
"chain_seeds": [
9301,
9302,
9303,
9304
],
"prior_predictive_seed": 13101,
"posterior_predictive_seed": 13291
},
{
"name": "low_threshold_balanced_drift",
"truth": [
0.9,
0.75,
0.7,
0.07
],
"trials": 400,
"data_seed": 4925,
"optimizer_seed": 74241,
"chain_seeds": [
10401,
10402,
10403,
10404
],
"prior_predictive_seed": 14101,
"posterior_predictive_seed": 14291
}
],
"objective_and_optimizer": {
"implementations": [
"direct JEAM ProjectedSphericalDiffusionModel.joint_lpdf",
"compiled HSSM blackbox logp"
],
"candidate_offsets": [
[
0.0,
0.0,
0.0,
0.0
],
[
0.12,
-0.1,
0.08,
-0.02
],
[
-0.12,
0.1,
-0.08,
-0.03
]
],
"optimizer": "scipy.optimize.differential_evolution",
"maxiter": 20,
"popsize": 15,
"polish": false,
"workers": 1,
"bounds": {
"v_x": [
-2.0,
2.0
],
"v_y": [
0.02,
2.0
],
"a": [
0.4,
2.0
],
"t_lower": 0.02,
"t_upper": "nextafter(minimum observed rt, -infinity)"
}
},
"execution": {
"sampler": "one pymc.Slice step per parameter in parameter_order",
"likelihood": "blackbox",
"backend": "pymc",
"chains": 4,
"tune": 1000,
"draws": 1000,
"cores": 1,
"blas_cores": 1,
"init": "adapt_diag",
"progressbar": false,
"compute_convergence_checks_during_sampling": true,
"compute_log_likelihood_during_sampling": false,
"prior_predictive_draws": 100,
"posterior_predictive_draws": 40,
"posterior_hdi_probability": 0.94,
"rt_quantile_probabilities": [
0.1,
0.5,
0.9
],
"data_policy": "Generate each dataset once through the public HSSM adapter, save its float64 bytes and SHA256, and reuse those exact bytes for optimizer and posterior inference.",
"trace_policy": "Save every returned DataTree to NetCDF immediately after sampling and before summaries or posterior prediction; record its SHA256 and byte count in the compact result.",
"predictive_angle_summary": "mean polar unit-vector components [mean(sin(response)), mean(cos(response))]",
"timing_policy": "Record optimizer, model build, sampling, posterior predictive, and total wall time descriptively with perf_counter; never make wall time a pass/fail criterion."
},
"preflight_gates": {
"prior_predictive": {
"all_values_finite": true,
"all_rt_strictly_positive": true,
"all_angles_in_closed_domain": true,
"rt_quantile_ratio_to_observed_lower": 0.05,
"rt_quantile_ratio_to_observed_upper": 30.0,
"ratio_probabilities": [
0.5,
0.9
]
},
"initial_point": {
"finite_joint_logp": true
}
},
"scientific_acceptance": {
"maximum_objective_absolute_error": 1e-08,
"maximum_optimizer_parameter_absolute_error": 1e-09,
"maximum_optimizer_objective_absolute_error": 1e-06,
"optimizer_recovery": {
"maximum_absolute_error": {
"v_x": 0.45,
"v_y": 0.45,
"a": 0.25,
"t": 0.08
},
"maximum_rmse": {
"v_x": 0.35,
"v_y": 0.35,
"a": 0.18,
"t": 0.06
}
},
"posterior_recovery": {
"maximum_rhat_exclusive": 1.01,
"minimum_bulk_ess_exclusive": 400.0,
"minimum_tail_ess_exclusive": 400.0,
"maximum_mcse_over_posterior_sd_exclusive": 0.05,
"minimum_94_percent_hdi_coverage_per_parameter": 0.75,
"minimum_overall_94_percent_hdi_coverage": 0.75,
"maximum_absolute_bias": {
"v_x": 0.3,
"v_y": 0.3,
"a": 0.15,
"t": 0.04
},
"maximum_rmse": {
"v_x": 0.4,
"v_y": 0.4,
"a": 0.22,
"t": 0.06
}
},
"posterior_predictive": {
"maximum_rt_quantile_absolute_error": 0.15,
"maximum_polar_unit_vector_component_absolute_error": 0.08
}
},
"reporting_and_deviation_policy": {
"result_path": "benchmarks/results/jeam_fixed_psdm_recovery_v1.json",
"raw_traces_committed": false,
"compact_result_committed": true,
"no_manual_chain_exclusions": true,
"no_interim_stopping": true,
"failed_sampling_is_a_recorded_result": true,
"infrastructure_retry": "Retry only a documented failure that occurs before a posterior is returned; retain failed-attempt metadata and rerun the complete affected scenario.",
"protocol_change": "Do not edit v1 after canonical execution begins. Correct a scientific or implementation defect by adding a new versioned specification and report v1 as superseded."
}
}
61 changes: 61 additions & 0 deletions benchmarks/specs/jeam_fixed_psdm_recovery_v1_addendum.json
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{
"schema_version": 1,
"addendum_id": "jeam-fixed-psdm-recovery-v1-archive-scope-1",
"study_id": "jeam-fixed-psdm-recovery-v1",
"status": "historical-preregistration-archived-promotion-blocked",
"document_role": "Post-hoc archival interpretation only; this file does not amend or preregister the v1 protocol.",
"immutable_protocol": {
"path": "benchmarks/specs/jeam_fixed_psdm_recovery_v1.json",
"original_freeze_commit": "c1c68ef3c0ebdf78b4a950c4e62e61bee55b0961",
"sha256": "2a9fabe13e612a59f7c2138e4e36ae4e01d4bde5e226c16c8572d5ebe3594198",
"replay_policy": "Replay the frozen bytes patch-identically; a replay is not a new preregistration."
},
"historical_execution": {
"hssm_stack_base_revision": "11fdc2236711f46d3bd6ba19589947fc20285ff1",
"hssm_runner_revision": "ebbd68ee6dcaad644505ae7f3739b7b1f0ba3794",
"jeam_revision": "1d7112757d8b2d27a31437255fc679194d39ab89",
"python_minor": "3.12",
"pytensor_floatx": "float64"
},
"current_safety_revision": {
"jeam_revision": "ede7a4f4faf226e4dae52c84dfb01012939cccdc",
"v1_recovery_rerun": false
},
"scope": {
"study_class": "seeded four-scenario recovery smoke, not a calibration study",
"model_contract": "ordinary scalar/intercept-only public-default HSSM model",
"formula_or_regression_support_evaluated": false,
"t_prior": "untruncated HalfNormal(sigma=2)",
"configured_t_bounds": [
0.0,
2.0
],
"prior_and_bounds_are_distinct_contracts": true,
"configured_t_bound_truncated_the_prior": false,
"posterior_likelihood_support": "t < minimum observed rt"
},
"known_v1_outcome": {
"result_path": "benchmarks/results/jeam_fixed_psdm_recovery_v1.json",
"result_commit": "d76f995d501603cc56f895e5fa429ce2be14e468",
"result_sha256": "cede87d5a5a2c9789939b66962ebb025b270a13966aa2d657d5b0cbb95e9c2c4",
"canonical_started_at_utc": "2026-08-17T04:15:03.738704+00:00",
"overall_pass": false,
"truth_in_hdi": 14,
"truth_total": 16,
"interpretation": "Recovery was not demonstrated under the frozen v1 design and budget; this is not evidence that fixed PSDM recovery is impossible."
},
"evidence_boundary": {
"dataset_hashes_recorded": true,
"trace_hashes_recorded": true,
"raw_datasets_retained_in_git": 0,
"raw_traces_retained_in_git": 0,
"raw_prior_predictive_draws_retained": false,
"raw_posterior_predictive_draws_retained": false,
"independent_raw_reverification": "blocked",
"fixed_psdm_public_support_or_promotion": "blocked"
},
"successor_policy": {
"v2a_and_v2b_require_new_preregistrations": true,
"mixing_and_identifiability_are_hypotheses_not_v1_conclusions": true
}
}
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