Joint likelihood for correlated observations O-4, O-5 (shared basis: S-4). Step 8 writes the single ## Likelihood block here; the member edges point back via group.
Likelihood
# CG-2 (HC-1) — ONE joint estimate over E-3 + E-4: O-4 and O-5 are presence and absence columns of the
# SAME census (S-4, May 2017-Nov 2019), so they are one witness, not two (rule 1). The pattern judged
# whole: "SARS-CoV-2-susceptible intermediate hosts (raccoon dogs, hog badgers) present in quantity at
# Huanan — 47,381 animals, 38 species — while the reservoir taxa (bats, pangolins) are entirely absent."
# Members in HC-1.hypotheses order: [H-1 Huanan market spillover, H-5 WIV research incident, H-6 residual].
# Anchored on H-1 = 1; H-5 and H-6 priced as ratios to it (rule 7). Each member is conditioned on strictly
# (process 2) — no prior-flavoured "lab leak is unlikely" leaks in here.
lik_census_H1 = 1.0 # anchor. H-1 (spillover at Huanan via live wildlife sold there) *entails* the
# first half: susceptible live mammals had to be physically on sale at Huanan, and
# the census confirms exactly that, in quantity, from pre-pandemic data collected
# before anyone had a thesis to defend. The second half cuts the other way but only
# within the zoonosis family: per A-2 (approved, checked), the bat/pangolin absence
# contradicts a necessary condition of the *direct* bat- or pangolin-sale route
# while contradicting no condition of the intermediate-host route that H-1's
# statement actually runs on. So the pattern removes H-1's simplest mechanism and
# supplies its needed precondition; net, still the member that predicts the whole
# pattern best, so it takes the anchor rather than a discount.
lik_census_H5 = 0.6 # 0.6x as expected as under H-1. Conditional on a WIV research incident, the
# species inventory of a Wuhan wet market is causally irrelevant — the pattern is
# then just the base rate for a large Chinese urban live-animal market. That base
# rate is not low: susceptible farmed mammals in the fur/meat trade are routine
# stock, and bats are essentially never sold for meat in central China, so the
# observed pattern is unremarkable under H-5. It is nonetheless less expected than
# under H-1, which forces the presence half rather than merely permitting it.
# Not below ~0.5: nothing in the pattern is improbable given H-5.
lik_census_H6 = 0.85 # 0.85x. Unconstrained member, so middling by default (rule 3), but nudged toward
# H-1 rather than to the midpoint: H-6's largest leg is a natural spillover
# upstream of Huanan (farmer/trapper/trader/transport) or at another Wuhan market,
# and that leg needs the same susceptible-mammal supply chain the census documents,
# while being positively comfortable with the reservoir taxa never reaching a
# retail floor at all. H-6's smaller non-WIV-research leg behaves like H-5. Kept
# below the anchor because H-6 only makes the pattern likely, it does not require
# it, and its research leg is indifferent to it.
t_census = 0.7 # cap = trust_score of S-4 = 0.8 (both observations, one source). Docked for two
# specific raw-data-to-observation weaknesses that step 6 explicitly left to be
# priced here (A-2's defeater probe): (i) the survey window ends Nov 2019 and the
# monthly vendor visits sample stock intermittently, so it does not directly
# observe what was on sale in the Nov-Dec 2019 window that matters; (ii) it records
# what surveyors saw and vendors reported over shop visits, not an exhaustive
# inventory, so a low-volume or clandestine taxon (exactly the case for a
# protected species like pangolin) could be under-recorded — an absence claim is
# more exposed to this than the presence claim, and the joint call inherits the
# weaker of the two. Not docked further: the counts are large, itemised and
# pre-registered against no origins thesis.
evidence("HC-1", ["O-4", "O-5"], [lik_census_H1, lik_census_H5, lik_census_H6], t=t_census)