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Alpha This system is experimental. Scores and classifications are early-stage research and may be unreliable. Methodology → |
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| Summary ~lite The article discusses the effectiveness of Recurrent Neural Networks (RNNs) in sequence processing tasks.
Lite evaluation by llama-4-scout-wai-psq · editorial channel only · no per-section breakdown available
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Longitudinal
· 5 evals | |
Audit Trail
10 entries | 2026-03-05 22:18 | eval_success | PSQ evaluated: g-PSQ=0.280 (3 dims) | - - | | 2026-03-05 22:18 |
eval
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Evaluated by llama-4-scout-wai-psq: +0.28 (Mild positive) | | | 2026-03-05 22:07 | eval_success | PSQ evaluated: g-PSQ=0.481 (3 dims) | - - | | 2026-03-05 22:07 |
eval
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Evaluated by llama-3.3-70b-wai-psq: +0.48 (Moderate positive) | | | 2026-03-01 21:57 | eval_success | Lite evaluated: Neutral (0.00) | - - | | 2026-03-01 21:57 |
eval
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Evaluated by llama-4-scout-wai: 0.00 (Neutral) 0.00 | | | reasoning ED, neutral tech tutorial | | 2026-03-01 21:52 | eval_success | Lite evaluated: Neutral (0.00) | - - | | 2026-03-01 21:52 |
eval
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Evaluated by llama-4-scout-wai: 0.00 (Neutral) | | | reasoning ED, neutral tech tutorial | | 2026-03-01 21:49 | eval_success | Lite evaluated: Neutral (0.00) | - - | | 2026-03-01 21:49 |
eval
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Evaluated by llama-3.3-70b-wai: 0.00 (Neutral) | | | reasoning Technical post on RNNs | | |
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