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.
Bibliographic record
Abstract
The recent surge of interest in mobile commerce (m-commerce) is fueled by consumer interest in being able to access business services or to communicate with other consumers anytime and anywhere. It is also motivated by the interest of the business community to extend their reach to customers at all times and all places. Businesses that aspire to succeed in this market must have a deep understanding of the interests and concerns of the mobile consumers in using wireless applications. With this in mind, this chapter provides an analysis of this emerging market from a consumer’s perspective. A consumer-centric m-commerce model outlining the various wireless interaction modes of the mobile consumer (m-consumer) is presented, followed by a discussion of the needs and concerns of the m-consumer. An m-commerce value network is then presented, outlining the roles of the different players within this industry. The various business applications developed to address m-consumer needs are then presented. Finally, a global m-commerce market overview is provided, and some future trends are outlined.Request access from your librarian to read this chapter's full text.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it