None None AppRovAlS Definitions
Bibliographic record
Abstract
When this Agreement refers to “you ” or “your”, it means the customer on whose Account Virtual Visa Debit has been enabled and whose name appears on the Reference Card. When this Agreement refers to “we”, “our ” and “us”, it means Royal Bank of Canada and companies that are part of RBC ® that may also issue a Virtual Visa Debit Number to you. “Account ” means your personal deposit account with us that is linked to the primary chequing position on your RBC Client Card and which is accessed when you make a debit transaction using Virtual Visa Debit. “Account Disclosures ” means the terms and conditions applicable to your Account as described in the RBC Royal Bank Disclosures and Agreements related to Personal Deposit Accounts booklet, as amended from time to time. “Client Card ” means your RBC Royal Bank Client Card that you use to access your Account. “Reference Card ” means the reference card we send you that contains your Virtual Visa Debit Number, and includes any replacements for that card. “Virtual Visa Debit Number ” means the 16-digit RBC Royal Bank Virtual Visa Debit number, when used alone or in combination with the expiry date and/or the CVV2 code indicated on the Reference
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 | 0.024 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.369 | 0.239 |
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; the direct Gemma label and the distilled Codex classifier 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".