Bibliographic record
Abstract
<p>What does the iTUTORS App look like and what will make it different and unique in a realm of educational Apps everywhere in the world? The core idea of this project is to create a marketplace for free or affordable education, where students or learners can meet with teachers and tutors who speak their own language regardless of where they are living. This platform will help both of them; the students to get free or affordable tutoring and the teachers to earn extra income to improve their living cost particularly in the war zones or poor communities. </p> <p>This project aims to build a new platform for providing online live tutoring for learners through a mobile phone App and make it accessible for anyone in the world. It will launch its first stage with free service in the Middle East, where many countries are suffering from armed conflicts. In Yemen and Syria, for example, this resulted in millions of students dropping from schools during the past few years. This project will create a platform in both forms of mobile Progressive Web App (PWA), compatible with Android and iOS devices, as well as a website to make it easy to access for any student or teacher by any device they have.</p>
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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".