Bibliographic record
Abstract
<p>Welcome to <span><a href="https://www.studioarash.com/" target="_blank" rel="noreferrer noopener">Studio Arash</a></span>, where love finds its perfect frame. We're a team of passionate <span><a href="https://www.studioarash.com/" target="_blank" rel="noreferrer noopener">Persian photographers in Toronto</a></span>, specializing in capturing the <span><a href="https://www.studioarash.com/blog-photography-videography" target="_self">beauty of weddings</a></span>. With our keen eyes and warm hearts, we turn your special moments into timeless treasures. Every photo we take tells a unique story of love and happiness, filled with laughter, tears, and all the emotions that make your day unforgettable. From the tender glances to the joyful embraces, we're dedicated to preserving every precious detail so you can relive your wedding day over and over again. Trust <span><a href="https://www.studioarash.com/" target="_self">Studio Arash</a></span> to create stunning images that will fill your heart with joy for a lifetime.</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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.074 | 0.009 |
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".