Bibliographic record
Abstract
© 2015, Mediterranean Center of Social and Educational Research. All rights reserved. Microsoft will take over Nokia's Devices and Services business, which includes both Smart Devices and Mobile Devices. In other words: The Lumia, Asha and X series are now all under Microsoft's umbrella. Design teams, supply chain, accessories, employees, developer relations and most of Nokia's manufacturing plants and testing facilities are also on Microsoft's side, as are most of the company's services like MixRadio, Store and more. Here, Nokia's mapping entity, is considered a separate business and isn't included as part of the deal, but Microsoft has agreed to a 10-year licensing agreement. On the one hand, Nokia’s decision to sell its mobile phone business to Microsoft is a Finnish tragedy. At Nokia’s best times, this giant contributed a quarter of Finland’s economic growth for past 10 years: it paid 23% of Finland’s corporate taxes. On the other hand, getting out of the mobile phone business sector is a probable blessing for Nokia. Life is tough nowadays for second-tier smartphone companies. Nokia’s global market share in the mobile phone market has dropped to 14 percent (from 19.9 percent a year ago, according to Gartner). The revenue of the company brings in from its devices and services division is down by more than half since 2008.This paper is aimed to show why Nokia had to be saved by someone external, both from the technological and financial point of view.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.217 | 0.117 |
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".