# Paper Gate Interpretation for Temporal Twins

This document is the paper-facing interpretation layer for the final Temporal Twins suite. It does **not** alter the raw diagnostic output in `results/paper_suite_20260503_202810/paper_suite_failed_checks.csv`. Instead, it reclassifies which checks are true hard gates versus descriptive or advisory findings for the paper.

## Gate Categories

### A. Hard Gates for `oracle_calib`

These are true benchmark validity gates for `temporal_twins_oracle_calib`:

- `matched_eval_pairs >=` required threshold
- `positive_rate = 0.5`
- `benign_motif_hit_rate = 0`
- `static_agg_auc` near `0.5`
- shortcut AUCs near `0.5`
- `XGBoost` near `0.5`
- `StaticGNN` near chance
- `AuditOracle` near `1.0`
- `RawMotifOracle` near `1.0`
- `SeqGRU` high
- `SeqGRU` shuffle delta strongly negative

### B. Hard Gates for Standard `easy` / `medium` / `hard`

For the standard `temporal_twins` difficulty ladder, the hard gates are the matched static-control checks:

- `matched_eval_pairs >=` required threshold
- `positive_rate = 0.5`
- `benign_motif_hit_rate = 0`
- `static_agg_auc` near `0.5`
- shortcut AUCs near `0.5`
- `XGBoost` near `0.5`
- `StaticGNN` near chance

These conditions verify that the benchmark remains shortcut-resistant and that fraud and benign twins are properly matched at evaluation.

### C. Advisory / Descriptive Checks for Standard `easy` / `medium` / `hard`

The following are **not** hard validity gates for the standard difficulty ladder:

- `MotifProbe`
- `RawMotifProbe`
- `SeqGRU` difficulty trend
- `SeqGRU` shuffle delta
- temporal-GNN performance
- temporal-GNN shuffle delta

These measurements are descriptive benchmark outcomes. They characterize difficulty and inductive bias; they do not determine whether the dataset itself is valid.

## Reclassified Final Paper-Suite Status

### `oracle_calib`

- hard gate passes: `5/5`
- `AuditOracle = 1.0000 ± 0.0000`
- `RawMotifOracle = 1.0000 ± 0.0000`
- `XGBoost = 0.5000 ± 0.0000`
- `StaticGNN = 0.5222 ± 0.0235`
- `SeqGRU = 1.0000 ± 0.0000`
- `SeqGRU delta = -0.5032 ± 0.0043`

Interpretation: `oracle_calib` passes the intended hard benchmark validation. The oracle/probe alignment is correct, static shortcuts are eliminated, and a causal sequence model recovers the signal with a large negative shuffle delta.

### `easy`

- static-control hard gates pass: `5/5`
- `XGBoost = 0.5000 ± 0.0000`
- `StaticGNN = 0.4946 ± 0.0128`
- `SeqGRU = 1.0000 ± 0.0000`
- `SeqGRU delta = -0.5003 ± 0.0096`

Interpretation: `easy` is a valid standard benchmark slice. Static shortcuts remain suppressed, and the temporal sequence signal is strong.

### `medium`

- static-control hard gates pass: `5/5`
- `XGBoost = 0.5000 ± 0.0000`
- `StaticGNN = 0.4922 ± 0.0203`
- `SeqGRU = 0.8391 ± 0.0174`
- `SeqGRU delta = -0.3337 ± 0.0191`
- `MotifProbe` and `RawMotifProbe` are lower by design and should **not** be treated as hard-gate failures

Interpretation: `medium` is **not** a failed dataset. It passes the static-control hard gates and shows the intended increase in temporal difficulty.

### `hard`

- static-control hard gates pass: `5/5`
- `XGBoost = 0.5000 ± 0.0000`
- `StaticGNN = 0.5026 ± 0.0198`
- `SeqGRU = 0.6876 ± 0.0128`
- `SeqGRU delta = -0.1883 ± 0.0111`
- lower probe and SeqGRU scores reflect intended difficulty

Interpretation: `hard` is **not** a failed dataset. It passes the static-control hard gates and intentionally weakens temporal recoverability relative to `easy` and `medium`.

## Reclassified Status Table

| Benchmark | Static-control hard gates | Probe/oracle status | SeqGRU status | Temporal-GNN status | Paper interpretation |
|---|---|---|---|---|---|
| `oracle_calib` | Pass `5/5` | `AuditOracle` and `RawMotifOracle` both near `1.0`; oracle behavior validated | `1.0000 ± 0.0000`, delta `-0.5032 ± 0.0043` | Underperformance is advisory only | Valid calibration benchmark with correct motif-label alignment and dead static shortcuts |
| `easy` | Pass `5/5` | `MotifProbe` / `RawMotifProbe` high, descriptive | `1.0000 ± 0.0000`, delta `-0.5003 ± 0.0096` | Advisory underperformance only | Valid standard benchmark with strong temporal signal |
| `medium` | Pass `5/5` | Lower probes are expected and descriptive, not failures | `0.8391 ± 0.0174`, delta `-0.3337 ± 0.0191` | Advisory underperformance only | Valid medium-difficulty benchmark with increased temporal challenge |
| `hard` | Pass `5/5` | Lower probes are expected and descriptive, not failures | `0.6876 ± 0.0128`, delta `-0.1883 ± 0.0111` | Advisory underperformance only | Valid hard benchmark with intentionally reduced temporal recoverability |

Temporal-GNN advisory failures are **not** benchmark failures. They support the paper finding that current temporal GNNs may not exploit order-sensitive temporal structure as effectively as a causal sequence model under matched static controls.

`medium` and `hard` are **not** failed datasets. They are intended difficulty levels in the Temporal Twins ladder. Their lower `MotifProbe`, `RawMotifProbe`, and `SeqGRU` values show increasing temporal difficulty rather than invalid benchmark construction.

## Notes on the Raw Diagnostic File

- `results/paper_suite_20260503_202810/paper_suite_failed_checks.csv` is retained unchanged as the raw diagnostic output.
- The raw file still reflects older gate semantics in which standard-mode probe thresholds and temporal-GNN thresholds appeared in failure columns.
- This document is the corrected paper-facing interpretation layer and should be cited when describing benchmark validity in the manuscript.