Research chronology.

Constructed the pure C autoregressive Transformer baseline (3.45M parameters) with pre-allocated buffer activation inspection and an interactive terminal REPL.

Scaled model parameter capacity from 3.45M to 23M in C; training throughput and stability observations reported in founder research log.

Identified character-level sequence length inflation; implemented C subword BPE tokenizer with author-reported ~3.8x sequence compression over sample text.

Implemented prompt-loss masking in pure C autograd, zeroing backpropagation gradients across prompt tokens to isolate assistant response loss.

Discarded 1.5M synthetic tokens containing logical drift; curated step-by-step scratchpad dataset to evaluate reasoning consistency.

Integrated Apple Accelerate BLAS (cblas_sgemm) and zero-allocation inner loops on Apple Silicon; compute bandwidth bounds reported in research log.

Formulated the mathematical simulation framework linking continuous norepinephrine infusion rates to acute hemodynamic response curves.

Modeled receptor-level pharmacodynamic curves translating drug plasma concentration into systemic vascular resistance and arterial pressure trajectories.

Encountered significant clinical forecasting failure when attempting to generalize predictions across distinct patients due to unmodeled autonomic tone variance.

Adding additional physiological channels failed to yield clinically meaningful MAP predictive improvements (+0.0078 mmHg, 95% CI crosses zero), though heart rate exposed compensatory baroreflex feedback.

Formulated the initial architectural proposal for transforming theoretical biological hypotheses into executable, computationally verifiable pipelines.

Outlined conceptual models for multi-agent simulation environments where models, instruments, and hypotheses interact within a state-managed scientific world.

Explored theoretical criteria and architectural requirements for bridging computational simulations directly with physical sensor acquisition pipelines.

Designed the transition from exploratory proof-of-concept scripts toward a structured research platform featuring Ed25519-signed .vlab containers and genesis database lineage.