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How sensitive is a focused meta-analysis of walking and jogging for depressive symptoms? A registered audit of a fixed public extraction pools 21 direct-comparison trials and 994 participants. Post-treatment Hedges g is -0.762, with a confidence interval from -1.203 to -0.321. Every leave-one-trial-out interval excludes zero, but the usual-care-only interval and the between-study prediction interval include zero. No included trial has an overall low-risk-of-bias rating. These conditional computations support neither a uniform treatment effect nor a treatment recommendation.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In the fixed Noetel et al. public extraction, the preregistered post-treatment direct comparison of walking/jogging with its specified active controls pools 21 trials and 994 participants at Hedges g=-0.762 (95% modified Hartung-Knapp confidence interval -1.203 to -0.321), all 21 single-trial-omission intervals remain below zero, but the overall prediction interval (-2.613 to 1.088) and usual-care-only confidence interval (-1.650 to 0.237) include zero and the overall-low-risk-of-bias subset has no trials, conditional on unchanged source outcomes and ratings.

We tested whether explicit flare and artifact controls improve recovery of simulated stellar self-lensing pulses in public Transiting Exoplanet Survey Satellite (TESS) light curves. A preregistered sample contains 100 stars, with 40 used for development and 60 for evaluation. At the same empirical background-trigger fraction of 10%, the development-selected controls recovered 269 of 540 pulses (49.8%), versus 239 (44.3%) for the lensing-template baseline. The difference is 5.6 percentage points, with a paired target-bootstrap interval from -10.6 to 26.7 percentage points. This pilot leaves a recovery benefit unresolved. Background triggers are not labeled false alarms, and this study makes no astronomical discovery claim.

• Published.Published: In a preregistered 100-target TESS Sector 1 pilot with 40 development and 60 evaluation stars, the development-selected flare/artifact control recovered 269/540 newly localized injected pulses versus 239/540 for the baseline at 6/60 un-injected target triggers per method, a 5.56-percentage-point difference with a paired target-bootstrap 95% interval of -10.56 to 26.67 percentage points, leaving a recovery benefit unresolved in this pilot.

Can unknown overlap between adverse-event terms change the direction of published composite-event estimates? We reconstructed the frozen registry comparisons and calculated every possible range of distinct affected participants consistent with the selected term counts. For adult serious suicidal behaviour, the resulting Mantel–Haenszel risk-ratio bounds are 1.712 to 2.1962; for adult serious suicidality, 1.2154 to 1.8476. The corresponding pediatric bounds are 1.0045 to 1.4773 and 1.8144 to 2.8091. All remain above the null. Unknown overlap therefore changes the magnitude but cannot reverse these fixed-data point estimates under the source's cohort and outcome definitions. These are identification bounds, not confidence intervals or estimates of causal treatment effects.

• Published, Reproduced.Published, Reproduced: In the frozen antidepressant registry dataset, conditional on source cohort selection, denominators, term coding, and absent-term imputation, sharp Mantel-Haenszel risk-ratio bounds relative to selected within-group event-count marginals are 1.7120261533 to 2.1961879882 for adult serious suicidal behaviour, 1.2154409158 to 1.8475901940 for adult serious suicidality, 1.0045047792 to 1.4773331886 for pediatric serious behaviour, and 1.8144436696 to 2.8090979871 for pediatric serious suicidality. Thus unknown participant overlap alone cannot reverse the direction of these fixed-data point estimates; these are not confidence intervals or causal treatment effects.

How much does scheduling a daily batch by historical grid intensity help when computing capacity and idle power are explicit? We evaluate seasonal clock-time profiles trained on 2023 public Great Britain data, with equal work and equal energy in every comparison. At 50% utilization, assigned carbon falls by 11.63% in 2024 and 12.81% in 2025 relative to uniform processing. Setting idle power to 50% of maximum power reduces these advantages to 3.88% and 4.27%. Some dates have higher assigned carbon after shifting. These results describe a fixed historical workload benchmark and an accounting signal; they do not measure avoided emissions.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In the frozen Great Britain daily-batch benchmark, seasonal profiles trained on 2023 data reduce assigned carbon versus uniform processing by 11.63% and 12.81% at 50% utilization with zero idle power in 2024 and 2025, but by 3.88% and 4.27% when idle power is 50% of maximum; at 87.5% utilization with zero idle power the reductions are 3.37% and 3.64%, while the half-utilization policy increases assigned carbon on 16 of 364 and 10 of 365 evaluation dates, respectively, conditional on the specified processor model and estimated average intensity data.