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Record W6913080157 · doi:10.5281/zenodo.840008

Analysis Of Research And Innovation - Operational Report

2017· article· en· W6913080157 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
FundersEuropean Commission
KeywordsInnovation managementResearch methodologyTechnology innovationProduction (economics)Quantitative analysis (chemistry)Raw data

Abstract

fetched live from OpenAlex

This report contains the operational analysis of research and innovation for the five reference countries of INTRAW (the U.S., Canada, South Africa, Australia and Japan). It describes and compares the different innovation systems, comprising – among others - the main role players, institutions and policies that drive research and innovation in the raw materials sector.

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)0.020
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.048
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0170.022
Science and technology studies0.0010.001
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.018

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 head0.272
GPT teacher head0.447
Teacher spread0.175 · 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.

Study designNot applicable
DomainEvaluation
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

Citations0
Published2017
Admission routes1
Has abstractyes

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