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Beginnings
When I was eight, I was a star soccer player on a state championship team. At the same time, I noticed something about my body that I could not reconcile with the anatomical reference images I was studying. The standard anatomical model showed the complete human body structure and musculature, with 600+ muscles. My body appeared different in ways I could see but couldn’t explain.
At shirtless soccer practices and at the local pool, I compared my body with other children. Unlike me, many appeared closer to the anatomical model. When I asked my parents, they said it was normal – my father and much of my family have a similar body structure and composition. When I asked my doctor, I was told I was within the normal‑weight BMI range and that nothing was wrong.
As I grew older, the difference became more pronounced. I was weaker, slower, and less stable. I continued to train consistently, lift weights, and pay close attention to my diet, but the underlying muscular difference did not change in a way that corresponded to the anatomical model. Eventually, I had to stop competitive sports—not because of a lack of discipline or effort, but because I could not develop the physical capacity required to compete at that level, and I had no framework for understanding why.
What if individuals can differ meaningfully from the expected anatomical model, yet the measurement system used to classify them cannot detect the difference?
In 1999, I began asking whether MRI could measure my muscle tissue directly. That question revealed deeper issues. MRI can directly measure skeletal-muscle, but there was no standardized baseline phenotype for human muscular development, no accepted standardized framework for directly measuring total muscle tissue, and no standardized population reference against which individuals could be compared. This remains true today.
Unable to find an existing research program addressing these problems, I began conducting independent research in 2003. Over roughly twenty‑five years, I have developed a proposed classification framework, including a baseline phenotype called the Standard Body Type One (BT1), along with assessment tools and an empirical dataset of 492 participants with integrated anatomical images and supporting variables.
Hypothesis
At present, MRI can directly measure skeletal-muscle, but there is no standardized baseline phenotype for human muscular development, no accepted standardized framework for directly measuring total muscle tissue (Heymsfield et al., 2026), and no standardized population reference against which individuals can be compared.
What happens when an institution has to make decisions about a biological characteristic for which it lacks a standardized reference framework? BMI brought the phenotype-classification blind spot into focus: for an individual to be scientifically classified relative to a biological standard, there must first be a defined reference against which that individual can be compared.
Yet a standardized baseline phenotype for human muscular development does not currently exist, even though science relies on an established anatomical model of the complete human body, including all 600+ muscles, throughout anatomy science.
There is an important distinction between describing variation and establishing a biological reference for interpreting variation. Descriptors such as “apple,” “pear,” “triangle,” “hourglass,” “rectangle,” and somatotype offer recurring visible body shapes, but they don’t provide a baseline for reference or scientifically establish the underlying biological structures producing those differences.
The established anatomical model provides the scientifically grounded starting point because it represents the structural organization of the human body: the skeleton and vertebrae, musculature, and associated anatomical structures. In practice, this model functions as an implicit anatomical reference throughout medicine and science. When a person visits a doctor, their physical structure is evaluated against this established model of normal human anatomy, allowing deviations, abnormalities, or pathology to be identified.
But the anatomical model describes the common structural organization of the human body; it does not explain the enormous biological variation that exists within that organization. It tells us what structures humans have, but not how those structures vary in development across individuals, what constitutes a baseline for that variation, or how differences in their development produce differences in body shape, composition, and physical capacity. The existence of the anatomical model, therefore, doesn’t eliminate the need for a standardized baseline phenotype—it establishes the structural foundation from which such a phenotype can be investigated.
What is missing is the ability to determine how much foundational muscle a person has as part of their natural underlying body composition. That information is fundamental to understanding an individual's metabolism, structure, physical capacity, and health.
Instead, two people with the same BMI but substantially different underlying phenotypes—one with significantly more natural muscle and one with significantly less—receive the same standardized classification, guidance, and general strategy despite fundamentally different body compositions, metabolic characteristics, and physical capacities. They follow the same diet, exercise, lifestyle, and behavioral protocol yet experience dramatically different outcomes.
The one with more natural muscle achieves the physical body shape they seek, while the other repeatedly fails despite comparable effort. When the existing framework cannot identify or measure the underlying biological differences, the explanation is all too often pushed back onto the individual: their failure must be caused by cheating, lying, miscalculating, or inability to follow the protocol. The absence of a standardized classification and measurement framework for muscular development is too often treated as irrelevant to these differences, when it could not be more relevant.
BT1 is not proposed as another arbitrary body shape category, but as an empirical phenotype corresponding to the established anatomical model of the human body. While this anatomical model serves as a foundational reference throughout science and medicine, its use as a candidate population-level baseline phenotype for human muscular development has never been formally evaluated.
The central question is not whether human bodies vary—they clearly do—but whether the established anatomical reference corresponds to a reproducible empirical pattern in real individuals. The proposed BT1 baseline phenotype operationalizes that anatomical model as a testable classification hypothesis:
If BT1 corresponds to a reproducible phenotypic pattern aligned with the standard anatomical model, then BT1-classified individuals should exhibit a coherent and empirically consistent set of objective anatomical indicators within the existing 492-participant dataset.
Why It Matters
Like muscular development, blood pressure varies substantially among individuals, but we don't say, “Why do we need blood-pressure reference ranges?” Instead, standardized clinical reference ranges allow that variation to be measured, classified, and interpreted. The AHA and ACC define normal adult blood pressure as below 120/80 mmHg, with standardized categories for elevated blood pressure and hypertension. Without such an established reference, clinicians would lack a common baseline against which to interpret individual measurements.
Muscle directly affects metabolism, glucose uptake, insulin sensitivity, movement, physical ability, body composition, and overall health. Yet people routinely encounter differences in body shape and composition that current categories cannot adequately explain. A person may lose weight, alter their diet, train extensively, and still be unable to produce a body shape that another person achieves with ease. These differences can also affect body image and mental health.
What accounts for the difference? Are some body structures more efficient or effective? What biological characteristics allow Usain Bolt to run at speeds that the vast majority of humans cannot?
Answering these questions requires seeing the whole body and comparing it’s structural scaffolding—skeleton, vertebral column, and musculature—to a standardized population-referenced baseline.
Without a baseline, large amounts of human variation remain structurally unclassified. We can describe body shape, measure height and weight, estimate body composition, and assign broad categories, but we lack a standardized biological reference for understanding how individual differences in muscular development relate to body composition, physical function, and health.
A baseline phenotype does more than classify muscle; it establishes a common biological reference for understanding differences in body structure, shape, muscular development, and composition across individuals and populations. It provides a foundation for investigating those differences through direct measurement rather than broad proxies or arbitrary descriptive categories.
The 492-participant dataset provides an empirical sample in which the proposed BT1 classification can be evaluated. The independent analysis will examine the distribution of BT1 and non-BT1 classifications, assess whether BT1 participants exhibit a coherent pattern of anatomical and phenotypic indicators, and determine whether the proposed classification exhibits sufficient empirical coherence and internal consistency to justify further MRI research.
The project is designed around independent scrutiny. The lead scientific researcher will conduct the primary scientific investigation, while three independent data scientists provide protocol review, independent analysis, and methodological assessment. Their analyses are designed to assess reproducibility and identify potential methodological weaknesses, discrepancies, or areas of disagreement. The scientific technical editor will provide independent scientific and methodological review, along with communication and editorial support, to ensure clarity, transparency, and methodological coherence.
Lead Scientific Researcher / Principal Investigator — $24,000
Develop the scientific record for peer-reviewed publication, clarify the existing dataset and classification framework, coordinate independent analyses and methodological assessment, interpret results, and prepare the manuscript and supporting materials for peer-review submission and follow-through to completion.
Independent Analyses — $16,000
A lead data scientist will establish and review the analytical protocol at the outset and conduct two methodological reviews during the project to ensure that prespecified procedures are followed appropriately. Two additional data scientists will independently execute the prespecified analyses using the existing dataset and classification framework, conduct robustness and sensitivity checks, and identify discrepancies, concerns, or disagreement.
Scientific Technical Editor — $3,000
Independent scientific and methodological review, including editing for clarity, accuracy, transparency, and reproducibility.
Peer Review Submission — $2,500
Publication of the resulting scientific record.
Post-Review Revision — $1,500
Revisions arising from external scientific review.
Additional Scientific Requirements — $3,000
Reserved for unforeseen scientific requirements.
Fees
Timeline — 8 Weeks, Then Peer Review and Finalization
Lead Scientific Researcher/Principal Investigator
3 Independent Expert Data Scientists have been identified and contacted (contract)
1 Independent Expert Scientific Technical Editor has been identified and contacted (contract)
Relevant Peer Review Journals have been identified and researched
The 492-participant dataset is complete and ready. Our track record is successful.
The most likely causes of failure are that the independent analysis of the existing 492-participant dataset may identify methodological limitations and/or may not contain sufficient information to support the proposed baseline Standard Body Type One (BT1) phenotype.
If the project fails to establish a reproducible empirical basis for BT1, the immediate outcome would be a clearer determination of what the existing dataset can and cannot support.
A negative result would therefore still provide useful scientific information: it would establish an evidence-based boundary around the current hypothesis and help determine how future research, including the planned MRI study, should proceed.
None.