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Record W2117916196

Autm U.S. Licensing Survey: Fy 2004 Survey Summary

2005· article· en· W2117916196 on OpenAlexaboutno aff
Ashley J. Stevens, Frances Toneguzzo, Dana Bostrom

Bibliographic record

VenueSSRN Electronic Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
Fundersnot available
KeywordsVenture capitalBusinessIntellectual propertyPrivate equityEquity (law)Investment (military)Fiscal yearSurvey data collectionAccountingMarketingFinancePolitical science
DOInot available

Abstract

fetched live from OpenAlex

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)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.198
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.015

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.

Opus teacher head0.012
GPT teacher head0.260
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2005
Admission routes1
Has abstractyes

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