Range Similarity and Satisfaction Measures for Buyers and Sellers in E-marketplaces
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
Price is the omnipresent factor in decision making of buyers and sellers when trading products in real and virtual marketplaces. However, since a fixed price can easily lead to unsuccessful negotiations, market players in practice often have price ranges in mind, which reflect possible negotiation concessions when finding potential buyer-seller matches. In this paper, we propose a price-range similarity measure that computes price-range overlaps based on buyers' maximum and sellers' minimum prices. We also propose two measures for computing a notion of satisfaction for buyers and sellers that is additionally based on their published prices. Our price-range similarity measure and the measures for satisfaction provide ranked seller/buyer lists for buyers, sellers, and the match-maker in an e-marketplace. These measures extend our earlier similarity algorithm towards a priced product/service compatibility measure for match-making between buyers and sellers.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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