Theory and mechanistic modeling

Drafted human-editable specification · v0.4.0 · no agent-performance claim

Epistemic purpose

• Create concepts, explanations, and derivations that make new relationships understandable or testable.

When this mode helps

• A concept, mechanism, or formal representation changes what can be explained or derived. Observation may precede or motivate theory.

Agent actions and representations

• Construct representations; propose mechanisms; derive consequences; inspect limiting cases and dimensions; compare explanatory scope; identify measurements that distinguish applications.
• Inputs: the question, available evidence and provenance, constraints, prior claims, and remaining budget.
• Outputs: inspectable artifacts, updated question/evidence state, and a claim record when a substantive claim is made.

Evidence and claim scope

• Assess mathematical validity under explicit assumptions separately from empirical adequacy. A sound derivation does not require an observation to have already occurred; its application to a system requires additional evidence.
• Distinguish a warranted decision at the time from a claim’s later assessed adequacy; append follow-up without rewriting the original record.

Transitions and stopping

• Use simulation when consequences need computation; enter hypothesis assessment when mechanisms have distinct observable consequences; revise representation after incompatibility.
• Neighbouring profiles: exploration, simulation, hypothesis, synthesis.

Characteristic failure

• Treat internal consistency as empirical truth; demand prospective prediction as the only route to theory; equate an elegant narrative with a derived consequence.

Human evidence and borrowing

• Wilson (1965) and Vine and Matthews (1963) are conceptual/physical cases; Dellsén (2016) and Bird (2007) supply contrasting accounts of scientific progress. The profile is a proposed operational interpretation.
• Cross-field comparison: Nersessian (2022) supplies a bioengineering comparison for building and adapting representations; record what assumptions survive the change of domain.
• Science of process/impact: Fortunato et al. (2018) reviews metascience at broader scales. No measured geoscience benefit of this theory procedure is claimed.
• The actions and transitions above are design hypotheses derived from these sources, not established optimal policies. Missing process chronology remains unknown.

Evaluation against past work

• Demonstrate a valid new consequence, explanatory connection, or capability relative to the task. Include a derivation with a hidden inconsistent assumption and a valid idealization with a limited empirical scope.
• Use the historical evaluation to choose a source record, preserve evidence boundaries, and assess a meaningful gain. A synthetic control tests a constructed case, not a historical discovery.
• Assessment definitions · Agent implementation

Bird, Alexander. 2007. “What Is Scientific Progress?” Noûs 41 (1): 64–89. https://doi.org/10.1111/j.1468-0068.2007.00638.x.

Dellsén, Finnur. 2016. “Scientific progress: Knowledge versus understanding.” Studies in History and Philosophy of Science Part A 56: 72–83. https://doi.org/10.1016/j.shpsa.2016.01.003.

Fortunato, Santo, Carl T. Bergstrom, Katy Börner, et al. 2018. “Science of Science.” Science 359 (6379). https://doi.org/10.1126/science.aao0185.

Nersessian, Nancy J. 2022. Interdisciplinarity in the Making: Models and Methods in Frontier Science. MIT Press. https://doi.org/10.7551/mitpress/14667.001.0001.

Vine, F. J., and D. H. Matthews. 1963. “Magnetic Anomalies Over Oceanic Ridges.” Nature 199 (4897): 947–49. https://doi.org/10.1038/199947a0.

Wilson, J. Tuzo. 1965. “A New Class of Faults and their Bearing on Continental Drift.” Nature 207: 343–47. https://doi.org/10.1038/207343a0.