Canonical Methodology & Provenance Directory

Composite velocity score calculated as normalized 30-day velocity across GitHub activity (35%), OpenAlex publications (25%), SEC Form D venture funding (25%), and USPTO patent filings (15%).

Logistic regression classifier predicting probability that an innovation reaches at least one confirmed commercial deployment event within 24 months, conditioned on current TRL, momentum, and foundational science citations.

Projected percentage disruption scale (0-100) combining total addressable market substitution potential, gross margin compression headroom, and unit cost arbitrage ratio relative to legacy incumbents.

Harmonic mean of capability benchmark (40%), commercial evidence count (35%), and academic/patent velocity (25%), bounded between 0% and 100%.

Normalized benchmark score (0-100) calibrated against empirical domain-specific leaderboards: LMSYS Arena for LLMs, MLPerf for accelerators, and IEEE/IEDM for physical semiconductor device density.

Quantified annual economic expenditure or labor cost currently spent on tasks directly addressed by this technology across relevant NAICS sector codes: sum(employment * mean_annual_wage * task_exposure).

Aggregate annual payroll exposure in occupational codes where task automation potential exceeds 50%: W_exposed = sum(employment_j * wage_j * task_overlap_j).

Cumulative undepreciated asset base rendered economically obsolete by emerging paradigm substitution: S(t) = Net PP&E * Disruption Rate.

Headcount in occupational codes where task-level exposure exceeds displacement threshold: H(t) = sum(employment_i * task_overlap_i).

Count of unresolved gating dependencies in the critical path across science, supply chain, and regulatory regimes.

Speculative financial multiple modeled via Carlota Perez Frenzy dynamics: captures enterprise valuation expansion, venture multiple inflation, and public equity market capitalization relative to installed baseline.

Real installed economic deployment modeled via logistic diffusion: P(t) = L / (1 + e^{-k(t - t_0)}), calibrated against physical adoption statistics (fabs, gigawatt capacity, units shipped).

Cumulative physical infrastructure capacity installed to support deployment (e.g. gigawatts of energized datacenter power, extreme ultraviolet lithography wafer capacity, transmission lines).

Dual-trajectory divergence: Delta(t) = F(t) - P(t), measuring speculative financial capital acceleration relative to installed production deployment.

Capacity spread between installed physical infrastructure and current productive utilization: Overhang(t) = I(t) - P(t). Identifies stranded capacity and timing risk.

Debt-to-Equity ratio (D/E = Total Debt / Book Equity) and Interest Coverage Ratio (ICR = EBIT / Interest Expense) for companies funding physical infrastructure buildout.

Algorithmic classification into Irruption, Frenzy, Synergy, or Maturity based on key factor cost deflation, speculative decoupling delta, and infrastructure buildout.

Predicted calendar year at which entrant learning-curve cost intersects incumbent cost threshold: C_entrant(Y) <= C_incumbent.

Empirical percentage cost reduction achieved for each doubling of cumulative manufacturing production volume: Learning Rate = 1 - 2^{-w}.

Discrete count of independently verified commercial adoption events meeting Rubric C criteria (dated, cited, deployed at scale in real production environments).

Count of unique, non-affiliated corporate, government, or academic entities with confirmed production deployments of the specified technology.

Census count of distinct commercial organizations tracked across the 6-stage AI revolution supply chain architecture (EDA/Foundry, GPUs, ASICs, Cooling/Power, Hyperscalers, Frontier Labs).

Census count of active applied technologies and innovations with verified commercialization paths, patent signals, or adoption evidence in the platform graph.

Total public equity market value calculated as the latest closing share price multiplied by diluted common shares outstanding as disclosed in the most recent SEC Form 10-Q/K.

Ratio of current market share price to GAAP diluted earnings per share (EPS) over the trailing four fiscal quarters.

Ratio of enterprise market capitalization to total GAAP net revenue generated over the trailing four fiscal quarters.

Theoretical takeover price of a company: Market Capitalization plus Total Short- and Long-Term Debt, minus Cash and Cash Equivalents.

Duration in calendar years between the publication date of foundational basic science discovery (t_basic) and the first verified commercial deployment at scale (t_commercial).

Ratio comparing the historical mean translation latency of physical science / biotechnology (~13.0 years) against computer science / modern AI foundation models (~2.2 years).

Cumulative global peer-reviewed citation count indexed across Web of Science Core Collection and OpenAlex academic corpora for landmark foundational research papers.

Annual rate of peer-reviewed publications and co-citations referencing a foundational discovery node, normalized against the discipline baseline mean over a rolling 3-year window.

Expert-audited score (0 to 5) evaluating empirical support across 8 independent pre-registered dimensions: primary source rigor, falsifiability, replication, analog match, code availability, data freshness, boundary bounds, and conflict disclosure.

Count of unique OECD/NSF academic scientific disciplines represented among foundational basic discovery nodes (Computer Science, Condensed Matter Physics, Molecular Biology, Mathematics, Materials Science, Electrical Engineering).

Non-parametric survival probability function S(t) correcting for right-censoring in pending, uncompleted technology gestation horizons: S(t) = prod_{t_i <= t} (1 - d_i / n_i).

Strictly proper scoring rule evaluating probability calibration. Mean squared error between predicted probabilistic forecast P(breakout) and binary empirical ground truth outcome Y ∈ {0, 1} across historical test cases: BS = (1/N) ∑ (p_i - y_i)².

Percentage of historical test cases where the model's binary decision threshold (p ≥ 0.50) correctly matched empirical ground truth breakout or flop status across blinded historical epochs.

Empirical unit cost of the techno-economic paradigm's core key factor (e.g. inference intelligence per token, energy per kWh, transistor per mm²), tracking cumulative experience curve deflation according to Wright's Law C(Y) = C_1 · Y^{-w} relative to emergence base year.

Perez frenzy phase multiple comparing total financialized enterprise value (EV) of paradigm leaders against the cumulative tangible capital stock (CapEx) and physical R&D deployed into real production capacity: M = ∑ EV_i / ∑ (CapEx_i + R&D_i).

Carlota Perez structural friction metric calculating the spread between technological deployment velocity P_tech(t) and statutory/regulatory institutional absorption capacity A_inst(t): Δ_inst(t) = P_tech(t) - A_inst(t).

Proportion of traditional, non-tech NAICS super-sectors (e.g. Agriculture, Discrete Manufacturing, Freight Logistics, Healthcare, Retail) that have deployed the general-purpose technology into active revenue production beyond pilot stage.

Prevailing gross profit margin percentage across incumbent and entrant firms in the defined market structure: (Revenue - Cost of Goods Sold) / Revenue * 100%.

Normalized Lerner Index measuring an industry's market power to price above marginal cost: L = (P - MC) / P, scaled from 0.0 (perfect Bertrand commodity competition at marginal cost) to 1.0 (unconstrained monopoly pricing umbrella).

Audited commercial contract value meeting US GAAP ASC 606 standards: non-binding LOIs, memoranda of understanding, and uncommitted pipeline are assigned zero weight (0.0). Only binding take-or-pay purchase orders with fixed delivery schedules and termination fees qualify.

Physical mass conservation audit comparing the projected annual consumption of critical minerals/feedstocks at full technology scale against annual global primary mining extraction reported by the USGS.

Maximum likelihood estimate of the heavy-tailed power law shape parameter alpha governing economic value capture and citation concentration: P(X > x) = (x_min / x)^alpha.

GDP contribution net of intermediate double-counting: (∑ created_frontier spend × VA_ratio) − (∑ destroyed_incumbent spend × VA_ratio), deflated to Chained 2024 USD via BEA GDP deflators. VA_ratio sourced from BEA Input-Output Use Tables by 4-digit NAICS code.

Symmetrical supply chain cascade: (∑ created_frontier × (B_k − 1)) − (∑ destroyed_incumbent × (B_k − 1)), where B_k is the Leontief backward multiplier for NAICS code k. Represents net change in orders placed on upstream supplier industries.

Physical capital rendered economically obsolete net of recoverable salvage value: ∑(stranded_capital_assets_usd × deflation_factor) − ∑(stranded_capital_assets_usd × salvage_recovery_rate × deflation_factor). Default salvage rate = 20% unless explicitly recorded.

Welfare gain to consumers from unit cost reduction via Harberger triangle approximation: CS = baseline_spend × (ΔP + 0.5 × |ε| × ΔP²), capped at 5× baseline_spend. Uses explicit consumer_surplus_gain_usd if recorded; otherwise computes from unit_cost_reduction_pct and price_elasticity (default ε = −1.5).

Laplace-smoothed ratio of gross created-frontier spend to gross destroyed-incumbent spend (Chained 2024 USD): CDR = (gross_created + $1B) / (gross_displaced + $1B). The $1B regularization constant prevents division-by-zero and ensures continuity near zero-displacement markets.

Aggregate public equity market capitalization of all companies whose primary revenue derives from the tracked technology node, summed across SEC EDGAR-listed entities linked to the technology's market_metrics record. Computed by market_metrics_builder.py from company_market_signals.

Aggregate venture capital and growth equity financing volume raised by companies in the technology ecosystem over the trailing 12 months, sourced from SEC Form D filings and PitchBook/Crunchbase cross-referenced records.

Census count of all demand-side market arenas cataloged in the UTP market lifecycle registry, spanning active and extinct markets across 7 economic sectors and multiple Perez techno-economic surges.

Sum of market_size_usd across all non-extinct markets in the UTP registry: ∑(market.market_size_usd) for markets where current_lifecycle_stage ≠ 'extinct_or_subsumed'. Sources: Gartner, IDC, WSTS, BloombergNEF, and UTP market sizing aggregation.

Unweighted arithmetic mean of typical_gross_margin_pct across all non-extinct tracked markets: ∑(market.typical_gross_margin_pct) / N_active. Each market's typical margin is sourced from SEC 10-K filings and CapitalIQ industry benchmarks.

Count of distinct competitive structure archetypes classified in the UTP market taxonomy, based on Tirole (1988) Theory of Industrial Organization: Natural Monopoly, Cournot Oligopoly, Bertrand Price War, Monopolistic Competition, Bilateral Monopsony, Contestable Commodity.

Count of direct asymmetric entrant-vs-incumbent substitution pairs tracked in the UTP lifecycle graph where an entrant technology is displacing or has displaced a legacy incumbent, based on Christensen disruptive innovation framework and UTP cost-parity crossings.