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Explains phenomena by assigning likelihoods to outcomes, acknowledging uncertainty in the effect.

Explains phenomena as the result of interactions and compositions of foundational elements.

Analyzes causal relationships by considering what would happen if the cause were not present.

Explains phenomena where the cause and effect occur simultaneously or within a minimal time frame.

Explains phenomena where higher-level system properties dictate the behavior of lower-level components.

Explores causal connections that unfold over time, assuming that causes precede their effects.

The capacities or abilities that different entities possess, which enable them to be the source of specific effects.

Occurs when an effect could be the outcome of multiple independent causes.

Explains phenomena by referring to conditions that must be present for an effect to occur.

Seeks to explain phenomena by understanding the mechanism through which the outcome is produced.

Explains actions or events by their intended purpose or goal, rather than the causes that brought them about.

A concept where the causes present are enough to account for the occurrence of the effect.

A relationship where the causality is passed down a chain, from one event to another.

Refers to inherent properties that tend to bring about certain effects under relevant conditions.

Explains phenomena based on the functions or roles of components within a system, often with a focus on why something occurs.

Quantifies causal effects by considering changes due to interventions in a system.

Explains phenomena by asserting that current state is the necessary consequence of previous states.

The generalizations or principles that describe regularities in the behavior of phenomena and predict how causes will lead to effects.

Refers to the process or sequence of events that causes one thing to lead to another in a particular context.