Research program
The Clinical Inquiry Ecosystem examines how observations become warranted knowledge, how physiological and movement mechanisms explain effects, how population causal knowledge is integrated, and how that knowledge becomes useful for one person through clinical instantiation.
A Boyer-informed model
Boyer’s model distinguishes scholarship by purpose. Discovery investigates how observations support inductive learning and warranted claims. Physiolog and Movement Systems develop complementary physiological and movement-mechanism knowledge. Integration brings evidence and mechanisms into population causal models, and practice instantiates that knowledge in reasoned engagement with one person.
Discovery scholarship
Examines how the language and methods of statistical inquiry constrain and organize what can be learned from observations. It develops critically evaluated evidence, estimates, uncertainty, and candidate knowledge about facts, processes, and causal relationships.
Explore stats4PT →Generative mechanisms
Develops physiological knowledge about how and why effects occur. This mechanistic account adds causal depth beyond observed interventions and outcomes.
Explore Physiolog →Movement knowledge
Studies how movement emerges and can be measured across interacting physiological, neural, muscular, mechanical, behavioral, task, and environmental systems. Its HMS Lab turns clinical observations into governed empirical questions without collapsing research, education, and care.
Explore Movement Systems →Integrative scholarship
Owns comprehensive model building: integrating evidence and mechanisms with context, provenance, uncertainty, and disagreement into curated population causal knowledge.
Explore Models4PT →Practice scholarship
Supports clinical instantiation: the disciplined application of population evidence, mechanisms, and movement knowledge to an inspectable working model of one person, revised as individual information changes.
Explore the Inference Engine →stats4PT evidence + Physiolog mechanisms + Movement Systems knowledgeModels4PT population causal knowledgeClinical Inference Engine patient-specific instantiation
Working principles
Population evidence and mechanisms constrain a working model of one person; they do not determine it without individual findings, context, uncertainty, and clinical judgment.
Evidence types, causal claims, concepts, measurements, and curation decisions remain explicit rather than being collapsed into one record.
Extraction can assist scientific work, but ontology resolution and human curation remain necessary before a claim enters the knowledge base.
Inference systems should expose evidence, assumptions, model versions, uncertainty, and reasoning steps to scientific and clinical review.
The boundary
The projects are conceptually aligned, independently owned, and not runtime-coupled.
stats4PT contributes evidence and warranted claims. Physiolog contributes physiological mechanisms, while Movement Systems and the HMS Lab contribute movement-domain knowledge, observations, and experiments. Models4PT performs the distinct integrative work of curating those contributions into population causal knowledge. The Clinical Inference Engine applies that knowledge through patient-specific instantiation; population knowledge alone does not determine care.
See project detailsThe aim is not to automate clinical judgment. It is to make the knowledge, assumptions, uncertainty, and inferential steps supporting that judgment more explicit.