Quantifying the Laboratory Effect in 3D Concrete Printing: A Meta-Analysis, Cross-Study Reliability Assessment, and Minimum Reporting Set

Process dependence is a defining feature of 3D concrete printing (3DCP), and any pooled inference across laboratories must quantify rather than ignore the laboratory effect. We assembled a harmonized corpus of 80 primary 3DCP studies (465 experiments and 1083 hardened mechanical observations) under PRISMA-style screening, applied controlled vocabularies and unit canonicalization, and estimated the share of variance attributable to the study cluster. The intraclass correlation coefficient is 0.77 (95% CI [0.59, 0.86]; 345 records and 40 studies), so more than three quarters of the dispersion in 28-day compressive strength lies between laboratories rather than between mixtures within the same laboratory. A 7-to-28-day calibration evaluated under leave-one-study-out (LOSO) cross-validation produces R2=0.625, MAE =8.67 MPa and RMSE =11.38 MPa, with 95% prediction intervals covering 96.9% of held-out observations; the band is wide enough (≈85 MPa at the median) that the calibration is suitable for early-screening of mixture and process candidates rather than for code-compatible structural verification. Most of this between-study scatter traces back to processing variables, curing regimes and loading directions that are inconsistently reported. We propose a three-tier Minimum Reporting Set (MSRS) and demonstrate, through a retrospective audit of the included corpus, that adoption is feasible at the entry tier (63% already comply) while higher tiers identify the metadata that must be added before pooled inference can support structural-design decisions for printed elements.