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Record W1492877851 · doi:10.3386/w20922

New Ideas in Invention

2015· report· en· W1492877851 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsUniversity of GuelphUniversity of Waterloo
FundersNational Institute on Aging
KeywordsComputer scienceEpistemologyMathematical economicsMathematicsPhilosophy

Abstract

fetched live from OpenAlex

A key decision in research is whether to try out new ideas or build on more established ideas. In this paper, we evaluate which type of work is more likely to spur further invention. When recent advances create superior opportunities for invention, their adoption as research inputs in the invention process promotes technological progress. The gains from pursuing such innovative research paths may, however, be very limited as new ideas are often initially raw and poorly understood. We determine idea inputs in invention based on the text of nearly every US patent granted during 1836-2010. We find that inventions that build on new ideas early are more likely to spur subsequent invention than inventions that rely on ideas of older vintage. Our results are important because they suggest a benefit from encouraging and supporting innovative research that tries out new ideas -avoiding stagnation in technological advance.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.067
metaresearch head score (Gemma)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0670.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.814
GPT teacher head0.643
Teacher spread0.170 · 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