Our main result was a null. Plants recorded as African malaria remedies scored no higher for predicted antimalarial chemistry than other medicinal plants (p = 0.49). Our leading explanation was the data gap: most of those plants have little or no chemistry in open databases, so a real signal could have been invisible. That explanation can be tested, so we tested it.
We repeated the whole analysis on Al-Abniah, a 10th-century Persian materia medica by al-Heravi, using Achundow's public-domain 1893 German translation. It suits the question for two reasons. It names malaria-like fevers outright: quartan fever, tertian fever (ghibb), and remedies given "before the fever attack", which is the recurring rhythm of malaria. Its plants are also well studied, with a median of 55 scored compounds per species against 11 in the African test. We wrote the test down and committed it before computing a single score. It used the same model, the same score and the same within-family permutation test. The retrained model reproduced our published predictions exactly before it scored anything new.
The result was null again. Across 246 species, the 27 fever plants scored no higher than the rest: a difference of −0.009, p = 0.76. This test could detect smaller effects than the African one (0.39 against 0.52 standard deviations). All four pre-registered checks were null too, including the subset most like malaria: the 8 species recommended for intermittent fevers gave p = 0.93.
With plenty of chemistry, explicit malaria-like fevers and a finer detection threshold, there is still no signal. The missing data in African plants is real, but it probably isn't why we found nothing. The likelier explanation is one we already listed among our limitations: a remedy can ease a fever without killing the parasite. Two traditions, a thousand years and a continent apart, now point the same way. The new section is live on the site at ethnohack-malaria.vercel.app/#s-second.
The plant identifications follow Achundow's commentary and were drawn up with AI assistance; they need an expert's review. Every prediction is a hypothesis for testing, not medical advice.