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ReScience C

A replication of piecewise parametric cubic curve fitting, useful for studying how a geometric approximation is constructed and checked.

Investigate Can the fitting procedure meet a fixed geometric error tolerance on evaluator-generated curves with different curvature?

ReScience C

A reproduction report about evapotranspiration and boreal wildfires, associated with the Ten Years Reproducibility Challenge.

Investigate Which reported statistic can be reconstructed from explicitly versioned, rights-cleared inputs and a documented R environment?

ReScience C

A replication concerning Bayesian transfer learning with informative priors.

Investigate How sensitive are posterior predictive errors to a deliberately misspecified prior under a fixed transfer-data budget?

ReScience C

A replication about reinforcement-learning-based program debloating and its relationship to unit tests and reduction procedures.

Investigate For a benign evaluator-authored toy program, how much reduction is possible without violating a held-out behavioral test suite?

ReScience

A replication of a pituitary-cell conductance model, with uncertainty quantification identified in source keywords.

Investigate Which bursting summary is robust to a prespecified parameter-uncertainty grid and solver refinement?

ReScience C

A replication about automated teaching formulated as planning in a partially observable decision process.

Investigate Can a bounded planner match an exact small-state reference on a fixed teaching objective?

ReScience C

A replication of an agent-based problem-solving model comparing groups with different ability and diversity compositions.

Investigate How often does each group-selection rule perform best across evaluator-generated landscapes and fixed random seeds?

ReScience C

A replication about Hamiltonian generative networks for learning dynamical structure.

Investigate How does long-horizon energy drift compare with trajectory error on a small analytic mechanical system?

ReScience C

A replication of Hamiltonian neural networks, connecting learned dynamics with an energy-based structure.

Investigate How do energy error and state error grow across a fixed extrapolation horizon?

ReScience C

A replication about hierarchical shrinkage as regularization for tree-based predictive methods.

Investigate How do shrinkage strength, prediction error and tree-based explanations vary under nested cross-validation?

ReScience

An R replication of a model of how learning can guide evolution, associated with the Baldwin effect.

Investigate How do prespecified summary statistics change when learning is disabled while the selection protocol is held fixed?

ReScience C

A replication about calibration and predictive uncertainty in deep neural networks, including mixup in its source keywords.

Investigate How do log loss, calibration summaries and selective-prediction error compare under a fixed validation and test split?