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"columnPairs": 90, "detectionAuc": 0.897, "utility": {"metric": "R\u00b2", "real": 0.871, "synthetic": 0.088}, "consistency": null, "membershipAuc": 0.491, "attributeInferenceRisk": 0, "singlingOutRisk": 0.003, "dcrShare": 0.493, "rareCopies": 0, "kWay": 67, "boostedDetectionAuc": 0.937, "precision": 0.785, "recall": 0.976, "authenticity": 0.696, "bestMembershipAuc": 0.491, "fitSeconds": 7.4, "rowsPerSecond": 26775}, {"method": "SDV GaussianCopula", "overall": 82, "columnShapes": 96, "columnPairs": 94, "detectionAuc": 0.747, "utility": {"metric": "R\u00b2", "real": 0.871, "synthetic": 0.507}, "consistency": null, "membershipAuc": 0.519, "attributeInferenceRisk": 0.06, "singlingOutRisk": 0, "dcrShare": 0.516, "rareCopies": 0, "kWay": 80, "boostedDetectionAuc": 0.841, "precision": 0.92, "recall": 0.979, "authenticity": 0.623, "bestMembershipAuc": 0.524, "fitSeconds": 0.5, "rowsPerSecond": 26775}]}], "caveats": ["The report is Ground's own. Overall is 35% column shapes, 35% column pairs and 30% detection; it doesn't include Rules, which checks the rules Ground detects and enforces, so Rules favors Ground by design.", "SDV CTGAN was trained for 50 epochs (its default is 300) to keep the run within a few hours on one CPU; more epochs would likely improve it. SDV GaussianCopula used its defaults. Both ran on SDV 2 with metadata detected from the training split.", "Differential privacy at \u03b5 = 3 keeps column shapes and the label mix, but a classifier can still tell DP rows from real ones (detection AUC 0.75\u20131.0): the noise breaks fine-grained structure, and rules can't be learned from the data without spending budget.", "Single runs with fixed seeds; differences of a point or two in Overall are within noise.", "MOSTLY AI ran locally from its open-source SDK (TabularARGN) with a 5-minute training cap per dataset; Synthcity ran with its plugin defaults. Gretel isn't included: it trains in Gretel's cloud, which would mean uploading the data to a third party.", "Where MOSTLY AI scores low we checked the rows, not just the numbers: on bank, 35% of its euribor3m values are off the 308-value grid the real rate sits on, which a classifier spots; on insurance it lost the smoker effect on charges (smokers average $14.2k vs $31.4k real), after 47 seconds of training, well under its 5-minute cap."]}