Financial and Legal Obligations that appear from Internet Traffic - Technology of Information and Communication Kosovo Case
Bibliographic record
Abstract
In this case study we have presented the comparison of the calls made by the clients to the telephone operator Y and the calls which have been transferred to the company responsible for the quiz through telephone calls. During this analysis we gathered calls from the Composite Call Data Record (CDR), the CDR partition is divided in two part, the CDR Originating part and the part of the CDR transit part.The part of the CDR Originating are as the showed following: Calling Party Number, Called Party Number, Date Fort Start Of Charge, Time For Start Of Charge, Time For Stop Of Charge and Chargeable Duration. The part of the CDR Transit part contains completely the same data that must be identical because it is the same call that additionally contains other information such as the name of the incoming route from which the call and outbound route or where the call came from is addressed by identifying its name. The data has been decoded by the hexadecimal system in the decade system to compare the numbers of calls, duration calls and time of calls. From the analysis that is done in this case study has come out there is a difference from the number of calls as well the duration of the calls that have been on the part of the customers to the operator Y and the calls directed by the operator Y in the contracting company X
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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 | 0.000 | 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 | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".