Trends in U.S. Venture Capital Investments Related to Energy: 1980 through the Second Quarter of 2010
Bibliographic record
Abstract
This report documents trends in U.S. venture capital investments over the period 1980 through the second quarter of calendar year 2010 (2010Q1+Q2). Particular attention is given to U.S. venture capital investments in the energy/industrial sector over the period 1980-2010Q1+Q2 as well as in the more recently created cross-cutting category of CleanTech over the period 1995-2010Q1+Q2. During the early 1980s, U.S. venture capital investments in the energy/industrial sector accounted for more than 20% of all venture capital investments. However subsequent periods of low energy prices, the deregulation of large aspects of the energy industry, and the emergence of fast growing new industries like computers (both hardware and software), biotechnology and the Internet quickly reduced the priority accorded to energy/industrial investments. To wit, venture capital investments related to the energy/industrial sector accounted for only 1% of the $119 billion dollars invested in 2000 by the U.S. venture capital community. The significant increase in the real price of oil that began in 2003-2004 correlates with renewed interest and increased investment by the venture capital community in energy/industrial investment opportunities. Venture capital investments for 2009 for the energy/industrial sector accounted for $2.1 billion or slightly more than 13% of all venture capital invested that year. The total venture capital invested in energy/industrial during the first two quarters of 2010 is close to $1.8 billion accounting for 17% of all venture capital investments during the first two quarters of 2010. In 2009, the aggregate amount invested in CleanTech was $1.8 billion (30% of the total US venture capital invested in that lean year) and for the first two quarters of 2010 US venture capital investments in CleanTech have already exceeded $1.9 billion (19% of all US venture capital investments made during the first half of 2010). Between 2004 and 2009, U.S. venture capital investments in energy/industrial as well as CleanTech have more than quadrupled in real terms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".