| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Examines the functional behavior of the heart, vasculature, lungs, airways, and blood—focusing on flow, pressure, gas exchange, transport, and regulatory control. Includes cardiac electrophysiology and mechanics, vascular resistance, ventilation, diffusion, perfusion matching, and autonomic/endocrine regulation. Excludes cellular-level biochemistry and whole-organism metabolism except where determined by CV–respiratory processes. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates from organ and tissue scales (mm–cm) to system-wide integration (multiple organ systems) across timescales from milliseconds (cardiac APs) to seconds/minutes (breathing cycles, heartbeats) to chronic physiological states (hours–days). |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Heart chambers, vessels, capillaries, alveoli, blood cells, hemoglobin, ventilation structures, respiratory muscles, receptors (baroreceptors, chemoreceptors), autonomic centers, and regulatory hormones. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Pressure, flow, resistance, compliance, elasticity, oxygen content, CO₂ content, ventilation rate, perfusion rate, cardiac output, stroke volume, airway resistance, and blood-gas partial pressures. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Pressure-driven vs diffusion-driven transport, systemic vs pulmonary circuits, elastic vs muscular arteries, ventilation modes, control systems (neural, endocrine), flow regimes (laminar vs turbulent), and gas-transport categories. |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Blood pressure, heart rate, stroke volume, cardiac output, vascular resistance, oxygen saturation, arterial/venous PO₂ and PCO₂, ventilation rate, alveolar volume, and perfusion distribution. |
| | Parameterization | How variables encode and represent the system’s state. | Physiological state encoded through pressure–volume loops, flow–pressure relationships, gas-exchange curves, ventilation metrics, oxygen–hemoglobin dissociation curves, and autonomic activity profiles. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Treating blood as a Newtonian fluid, modeling vessels as uniform elastic tubes, assuming perfect ventilation–perfusion matching, treating cardiac contraction as uniform, or simplifying gas exchange to single-compartment models. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Idealizations fail under turbulent flow, heart failure, vascular disease, heterogeneous lung pathology, high-altitude physiology, shunts, or extreme autonomic modulation. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Assumes predictable pressure–flow behavior, stable respiratory mechanics, deterministic cardiac conduction, consistent gas-diffusion laws, and interpretable autonomic/endocrine control patterns. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes vessels and airways maintain characteristic mechanical properties, blood-gas equilibria reflect consistent physicochemical laws, and reflex/regulatory responses remain coherent under physiological conditions. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Hemodynamics, ventilation mechanics, gas-exchange dynamics, and regulatory feedback must align without contradiction across organ systems and physiological states. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Entities (heart, vessels, alveoli), variables (pressure, flow, gases), and assumptions (pressure–flow coupling, diffusion laws, regulatory control) must integrate into a unified CV–respiratory framework. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Blood pressure waves, ECG traces, heart sounds, airflow patterns, lung volumes, oxygen/CO₂ levels, ventilation rate, perfusion distribution, pulse oximetry signals, and gas-exchange curves. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Minimum measurable pressure change (mmHg), smallest resolvable CO₂/O₂ change, sensitivity thresholds of pulse oximeters, minimal detectable airflow change, and resolution limits of spirometry and ECG instrumentation. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | mmHg (pressure), L/min (flow/ventilation), bpm (heart rate), L (lung volumes), SpO₂ (%), PaO₂/PaCO₂ (mmHg), cardiac output (L/min), and compliance/resistance units. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | ECG, sphygmomanometers, arterial catheters, spirometers, plethysmographs, capnographs, pulse oximeters, blood-gas analyzers, Doppler ultrasound, echocardiography, ventilators, and metabolic carts. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Definitions for “tidal volume,” “stroke volume,” “cardiac output,” “end-diastolic volume,” “functional residual capacity,” “ventilation–perfusion ratio,” and “airway resistance,” based on instrument-specific criteria. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Standard measurement procedures such as ECG lead placement, arterial pressure catheterization, spirometry testing maneuvers, blood-gas sampling, Doppler flow assessment, and mechanical-ventilation calibration workflows. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Continuous hemodynamic monitoring, breath-by-breath airflow recording, serial blood-gas sampling, repeated cardiac output assessments, ventilation-cycle tracking, and controlled exercise/respiratory-challenge protocols. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Selecting cardiac cycles, breath cycles, airway segments, vascular regions, patient states (rest/exertion), and replicate measurements to ensure representative hemodynamic and respiratory datasets. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Pressure waveforms, ECG tracings, flow–volume loops, inspiratory/expiratory flow curves, blood-gas panels, Doppler flow profiles, oxygen-saturation traces, and mechanical-compliance data. |
| | Resolution | The granularity or precision with which data is captured. | Temporal resolution: ms-scale for ECG/pressure; breath-by-breath for ventilation; spatial resolution for ultrasound/echo; concentration resolution for blood gases; mechanical resolution for compliance/elasticity. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Calibration of pressure transducers, spirometers, blood-gas analyzers, echocardiography Doppler settings, oximeter baselines, and ventilator flow/pressure sensors. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Errors from catheter drift, ECG noise, incomplete spirometry effort, motion artifacts, sensor misalignment, analyzer drift, patient variability, and ventilation-system mechanical error. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Core physiological relationships such as the pressure–flow–resistance law, Frank–Starling relationship, Laplace’s law for vessel tension, oxygen–hemoglobin dissociation dynamics, compliance curves, and ventilation–perfusion relationships. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Stable properties like resting cardiac cycle phases, characteristic blood-gas equilibrium behavior, conserved dissociation-curve shape, predictable vessel elasticity ranges, and stereotyped heart-sound patterns. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Mechanisms include cardiac electrical conduction, muscle contraction mechanics, vascular smooth-muscle regulation, diffusion and convection in gas transport, chemoreceptor/baroreceptor reflexes, and autonomic/endocrine modulation. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Sequential processes such as electrical depolarization → mechanical contraction → pressure generation → forward flow; or ventilation → alveolar diffusion → perfusion → systemic gas delivery. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Key terms include cardiac output, stroke volume, preload, afterload, resistance, compliance, ventilation, perfusion, diffusion capacity, partial pressure, and respiratory drive. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Blood vessels (arteries/arterioles/capillaries/veins), respiratory zones (conducting vs respiratory), flow regimes, autonomic inputs (sympathetic/parasympathetic), and control modes (neural/endocrine/local). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Ohm-like hemodynamic law (Flow = ΔP/R), gas law/diffusion equations (Fick’s law), compliance formulas, pressure–volume loop equations, alveolar gas equations, and oxygen–hemoglobin dissociation equations. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Cardiac cycle models, multi-compartment circulation models, lung-mechanics models, diffusion–perfusion models, baroreflex and chemoreflex control models, and integrated cardiorespiratory simulations. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Single-compartment lung models, uniform-vessel models, linear compliance assumptions, Newtonian blood approximations, idealized V/Q matching, and simplified cardiac or vascular geometry. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Valid under normal physiology, moderate pressure/flow ranges, healthy tissue properties; break down under turbulent flow, pathology (HF, COPD), extreme altitude, shunts, fibrosis, or autonomic dysfunction. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Cardiopulmonary coupling theory, integrated control of oxygen delivery, autonomic–mechanical feedback loops, whole-system gas-transport models, and total-body homeostasis frameworks. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Strong ties to biomechanics, electrophysiology, pulmonary medicine, vascular biology, anesthesiology, exercise physiology, and systems biology via shared flow, pressure, diffusion, and regulatory principles. |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating preload/afterload, altering vascular resistance, applying pharmacologic agonists/antagonists, modifying inspired gas composition (O₂/CO₂), pacing the heart electrically, or adjusting mechanical ventilation to test causal hemodynamic and respiratory mechanisms. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Recording natural variations in HR/BP, spontaneous breathing cycles, blood-gas fluctuations, cardiac conduction patterns, and perfusion changes without applying controlled perturbations. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Evaluating predictions about flow–pressure relationships, gas-exchange efficiency, reflex responses, cardiac output regulation, and ventilation–perfusion matching using structured physiological challenges or pharmacologic tests. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating hemodynamic measurements, spirometry, blood gases, flow/pressure recordings, perfusion scans, and cardiac output assessments across subjects, sessions, and physiological conditions. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Using regression models, time-series analysis, mixed-effects models, pressure–volume loop analysis, diffusion-capacity estimation, spectral analysis of respiratory or ECG rhythms, and Bayesian physiological modeling. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing hemodynamic models, lung-mechanics models, gas-diffusion models, autonomic control models, and integrated cardiorespiratory simulations for fit, stability, and predictive accuracy. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying noise from catheter drift, sensor miscalibration, airflow-turbulence artifacts, ECG motion noise, incomplete respiratory effort, and variability in metabolic or perfusion-dependent measurements. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Standardizing breathing maneuvers, blinding waveform analysis, calibrating pressure/flow sensors, controlling subject posture, minimizing movement artifacts, and maintaining consistent ventilator settings. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent evaluation of hemodynamic waveforms, gas-exchange analyses, cardiac output models, V/Q interpretations, and regulatory-curve claims through peer review and cross-lab replication. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating models of cardiac mechanics, vascular regulation, respiratory mechanics, diffusion–perfusion coupling, or autonomic control when empirical observations contradict classical frameworks. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full reporting of measurement settings, ventilator parameters, catheter calibration files, ECG filtering methods, waveform-processing algorithms, and assumptions in hemodynamic/gas-exchange models. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Ensuring humane treatment of subjects, minimizing invasive procedures, honest reporting of physiological data, preventing falsification of waveforms, and adhering to clinical/experimental safety standards. |