[RETRACTED] https://mavi-bihard.clubeo.com/page/truly-keto-gummies-reviews-works-or-safe.html v1
Bibliographic record
Abstract
[RETRACTED] https://mavi-bihard.clubeo.com/page/truly-keto-gummies-reviews-works-or-safe.html https://techplanet.today/post/truly-keto-gummies-reviews-go-keto-gummies-1 https://techplanet.today/post/truly-keto-gummies-reviews-truth-revealed-results-and-opinion https://www.facebook.com/Truly-Keto-Gummies-Reviews-united-states-107939991972052 https://www.facebook.com/Truly-Keto-Gummies-Reviews-107836105316749 https://www.facebook.com/Greenhouse-pure-cbd-gummies-106026285496651 https://www.facebook.com/Pure-cbd-gummies-102569779181929 https://www.facebook.com/Pure-Calm-CBD-Gummies-UK-110068101746215 https://www.facebook.com/Pure-Calm-CBD-Gummies-103699065729694 https://www.facebook.com/Condor-cbd-gummies-amazon-109872925101799 https://www.facebook.com/Condor-Cbd-Gummies-Amazon-Reviews-111154134970981 https://www.facebook.com/Condor-cbd-gummies-110150831737139 https://www.facebook.com/Condor-cbd-gummies-1-million-happy-customer-107932995294638 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https://www.facebook.com/Prime-Shape-Keto-Gummies-united-states-vs-canada-107093518717936 https://www.facebook.com/Via-Keto-Apple-Gummies-Canada-100786462698740 https://www.facebook.com/Via-Keto-Apple-Gummies-Reviews-Canada-106806105418394 https://www.facebook.com/Goketo-Gummies-Reviews-105851852183099 https://www.facebook.com/Go-keto-Gummies-108585138572447 https://www.facebook.com/InfinuityCBDGummiesReviews/ https://www.facebook.com/InfinuityCBDGummiesPrice/ https://infinuity-hopkins.clubeo.com/page/infinuity-cbd-gummies-scam-or-legit-improve-your- health.html https://techplanet.today/post/infinuity-cbd-gummies-reviews-are-the-product-fake-or-real https://techplanet.today/post/infinuity-cbd-gummies-reviews-scam-or-legit-updated-result-2022 https://analogmotion.com/community/forums/forums/5091-show-shine/topics/59390-infinuity-cbd-gummies-does-it-work-what-they-won-t-tell-you 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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 | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.853 | 0.874 |
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".