Autm U.S. Licensing Survey: Fy 2004 Survey Summary
Bibliographic record
Abstract
This annual survey by The Association of UniversityTechnology Managers is a summary of technology licensing and related performance information for academic and non profit institutions, as well as asmall number of patent management and investment firms, for the fiscal year2004. In a departure from previous years' survey summaries, this report summarizes and discusses only the data for the United States. Survey results for Canada are summarized and discussed in a separate report, although the Canadian survey totals are included in the report's appended tables. Quantitative information from AUTM members using the AUTM Licensing Survey instrument is presented. Survey results are summarized for the 198 United States universities, hospitals, institutes and technology investment firms responding. Questions new for 2004 asked about types of intellectual property disclosed, types of initial patent applications, number of inventionsdisclosed, and funding source for startups. Results are summarized following the order of the technology transfer process: resources devoted to technology transfer, research support,invention disclosures, patent applications, issued patents, licensing information, startup companies, source of funding, and equity holdings. This year's report included brief discussions of the social impact of several specific projects. Findings for 2004 show steady growth in the six percent range for most performance measures. There is clear evidence of recovery from market conditions that hindered startups in the previous two years as a result ofchanges in capital markets. Venture investments stabilized after three years of decline, and the initial public offering market improved. In terms of gap funding mechanisms, individuals provided initial funding foralmost 50 percent of startups; only 20 percent of companies could attract venture capital. Appendices include survey methodology, definitions, the survey form, and survey totals for U.S. and Canadian institutions. (JSD/TNM)
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.015 |
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".