Bibliographic record
Abstract
abc corporation 211-12, 214-15 billing system 213 growth strategy of 208-9 service performance 209-10 abstract-entity-interaction-outcome-Universals (aeioU) framework 516 aiMMS concept of 264 air france 105 akaike's information criterion (aic) 62 amazon.com322, 343-4, 399, 428 recommendation system of 400 review system of 418 american customer Satisfaction index (acSi) 154 american express online presence of 148-9 apple, inc.229, 287, 420, 428 growth of 278 personnel of 352, 482-3 products of 396, 399, 481-5 attitudinal equity (ae) 177 audi ag virtual Lab 419 australia new South Wales education department 595-6 bayesian information criterion (bic) 62 bizrate 322 bose corporation 482 brazil 529 curitiba 580 british Petroleum (bP) deepwater Horizon disaster (2010) 422 business-to-business (b2b) services 13, 17-19, 22, 30, 56, 65, 176, 184, 187, 189, 207, 370, 377-8, 478 consultation 234 failed relationships 29-30 growth strategies in 370-71, 376 role of service encounters in 229, 231 small 29 business-to-consumer (b2c) services 17-18, 22-3, 97, 231, 382, 478 direct marketing 27 examples of 13 call detail records (cdr) use of in creation of networks 110 canada government of 595 cash flow 23, 144 discounted 28, 123 patterns of 11, 14 sources of 24-5, 27 variation in 28-30 catalina 404-5 china 413, 420-21, 529 beijing 413 citizens 581 co-creation efforts of 580, 582-3, 589-91, 593-4, 597 dialogue, access, risk benefits, and transparency (dart) 588-9 closed-loop marketing (cLM) 398-9, 404 adaptive personalization systems (aPS) 403-11 mobile 402 personalization 401-3 recommendation systems 399-401 research and development in 398 co-creation initiatives 590, 592-3, 601-4 citizen efforts of 580, 582, 589-91, 593-4, 597 concept of 583-4, 602 examples of organisations 594-7 management of 604-5 service 581, 598, 600, 602
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.010 |
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".