Triennial Report 2015 - 2017 - Metrology Research Institute
Bibliographic record
Abstract
This triennial report summarizes the research carried out at the Metrology Research Institute of Aalto University during period 2015 - 2017. Close collaboration between the Institute and MIKES Metrology of VTT Technical Research Centre of Finland Ltd has continued after the merge of MIKES to VTT in the beginning of 2015, leading to many research highlights. An article on “Advantages of white LED lamps and new detector technology in photometry” by Pulli et al was published in Light: Science and Application (4, e332, 2015), a journal with high impact factor of 14.6. Another highlight of 2016 was the start and excellent results of the European PhotoLED project (Future photometry based on solid state lighting products), coordinated by Tuomas Poikonen at VTT and Aalto University. Finally, several oral contributions in top-class international conferences were achieved by researchers of the Institute: One invited talk and four oral contributions in the NEWRAD Conference (Tokyo 2017) and five oral contributions in the CIE Conference (Korea 2017).
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.027 |
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; both teacher heads agree on what is shown here.
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".