Lots of other problems with it too. Why is there any last-universal-common-ancestor in this scenario? You would want to drop a full ecosystem with millions of different organisms, each with different FEC shards of data. If you can deliver some bacteria to a virgin planet, you can deliver multiple kinds of bacteria, not just one. Yet, genetics finds that there's a LUCA (not that much of LUCA survives in current genomes).

• Chirin no Suzu/Ringing Bell (review)
• Soul Eater (review)

• The Bridge to Lucy Dunn, Exurb1a (review)

• Modern Japanese Diaries, Donald Keene (review)

Everything is heritable:

• "Genome-wide association study of antisocial personality disorder", Rautiainen et al 2016 (GWAS hits on crime)
• "The Causal Effects of Education on Health, Mortality, Cognition, Well-being, and Income in the UK Biobank", Davies et al 2016
• "Shared genetic aetiology of puberty timing between sexes and with health-related outcomes", Day et al 2015 (Most correlations are bad, as predicted by life cycle theory.)
• "Genomic analyses for age at menarche identify 389 independent signals and indicate BMI-independent effects of puberty timing on cancer susceptibility", Day et al 2016b
• "Evidence that low socioeconomic position accentuates genetic susceptibility to obesity", Tyrrell et al 2016

Politics/religion:

• "'Superbug' scourge spreads as U.S. fails to track rising human toll" (The weakness of US public health statistics on the spread of antibiotic resistance.)
• "The Iron Law Of Evaluation And Other Metallic Rules", Rossi 1987
• "The Terrorism Delusion: America's Overwrought Response to September 11", Mueller & Stewart 2012
• "The Disappeared: How the fatwa changed a writer's life"
• Malcolm X's life of crime

AI:

• "WaveNet: A Generative Model for Raw Audio"
• "Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning", Zhu et al 2016 (video)
• "Deep Neural Networks for YouTube Recommendations", Covington et al 2016
• "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network", Ledig et al 2016
• "Hyper Networks", Ha et al 2016 (blog)
• "Generative Visual Manipulation on the Natural Image Manifold", Zhu et al 2016b
• "Challenges for Brain Emulation: Why Is It So Difficult?", Cattell & Parker 2012
• NN architectures depicted graphically

Statistics/meta-science/mathematics:

• "Saving Science: Science isn't self-correcting, it's self-destructing. To save the enterprise, scientists must come out of the lab and into the real world."
• "Probing the Improbable: Methodological Challenges for Risks with Low Probabilities and High Stakes", Ord et al 2008
• "Predicting Experimental Results: Who Knows What?", DellaVigna & Pope 2016
• "The Solution of the n-body Problem", Diacu 1996
• "If you went outside and lay down on your back with your mouth open, how long would you have to wait until a bird pooped in it?"
• /r/estimation

Psychology/biology:

• "Morphometricity as a measure of the neuroanatomical signature of a trait", Sabuncu et al 2016 (Heritability/variance component estimation generalized to brain volume/thickness: demonstrates that brain structure can predict a large fraction of variance among Alzheimers & aging (~1), IQ (0.95), etc, and so those traits have causal relationships (of some sort) with brain volume/thickness. While the causal relationships may not turn out to be interesting (we already knew brain volumes and thicknesses are catastrophically affected by aging and Alzheimer's), it does at least imply that as brain imaging datasets get larger, they will get ever better at predicting whether a subject has Alzheimers or how intelligent a person is. Hopefully we'll see variance components taken seriously outside of genetics. If power analysis tells you whether you have enough light to find the needles in the haystack, variance components can tell you whether there are even any needles to look for.)
• "Treatment of Psychopathy: A Review of Empirical Findings", Harris & Rice 2006
• "How to Raise a Genius: Lessons from a 45-Year Study of Super-smart Children"
• "Does Reading a Single Passage of Literary Fiction Really Improve Theory of Mind? An Attempt at Replication", Panero et al 2016
• "Failing Your Goals with Beeminder"
• "Evidence That Computer Science Grades Are Not Bimodal", Patitsas et al 2016
• "Thomas Jefferson Defends America With a Moose"
• "Syphilis in Renaissance Europe: rapid evolution of an introduced sexually transmitted disease?", Knell 2004
• "How to confuse a moral compass: Survey 'magic trick' causes attitude reversal"
• "Melatonin Treatment Effects on Adolescent Students' Sleep Timing and Sleepiness in a Placebo-Controlled Crossover Study", Eckerberg et al 2012

Technology:

• "Capacity-approaching DNA storage", Erlich & Zielinski 2016 (If DNA storage gets real-world usage, it might help accelerate the DNA synthesis cost-curve, and we could get whole genome synthesis years before I project!)
• "Breakthrough silicon scanning discovers backdoor in military chip", Skorobogatov & Woods 2012
• "Fully Countering Trusting Trust through Diverse Double-Compiling", Wheeler 2009
• "Turning 8-Bit Sprites into Printable 3D Models"
• "Magic: the Gathering is Turing Complete"

Economics:

• "Do Immigrants Import Their Economic Destiny? How migration shapes the prosperity of countries"
• "When It Rains It Pours: The Long-run Economic Impacts of Salt Iodization in the United States", Adhvaryu et al 2016
• "Signaling and Productivity in the Private Financial Returns to Schooling", Bingley et al 2015 (As I've mentioned before, even if you aren't all that interested in heritability or genetic correlations, twins and family studies are still vital for causal inference in economics/medicine/sociology because they control for so many things.)
• "China's Gold Rush in the Hills of Appalachia: Buyers in Hong Kong and Beijing are paying top dollar for wild American ginseng, fueling a digging frenzy that could decimate the revered root for good"
• "Good Policy or Good Luck? Country growth performance and temporary shocks", Easterly et al 1993
• Experience curve effects
• "Ramit Sethi and Patrick McKenzie on Getting Your First Consulting Client"
• "Lehman Brothers, We Heard You Were Dead"

Philosophy:

• "Logical Induction", Garrabrant et al 2016
• "Not By Empathy Alone"
• "The Wisest Steel Man"

Fiction:

• Ted Chiang:

  • "Exhalation"
  • "The Merchant and the Alchemist's Gate"

If I get at least 100 responses, then that will help narrow down the primary question of overall catnip response rate adequately in combination with the existing meta-analysis. I expect to get at least that many, and in the worst case I do not, I will simply buy the survey responses on Mechanical Turk.

The secondary question, Japanese/Australian catnip rates vs the rest of the world, I do not expect to get enough responses since the power analysis of the 60% vs 90% (the current average vs Japanese estimates) says I need at least 33 Japanese respondents for the basic comparison; however, Mechanical Turk allows you to limit workers by country, so my plan is to, once I see how many responses I get to the regular survey, launch country-limited surveys to get the necessary sample size. I can get ~165 survey responses with a decent per-worker reward for ~\$108, so split over Japan/Korea/Australia, that ought to be adequate for the cross-country comparisons. (Japan, because that's where the anomaly is; Korea, to see if the anomaly might be due to a bottleneck in the transmission of cats from Korea to Japan back in 600-1000 CE; Australia, because a guy on Twitter told me Australian cats have very high catnip response rates; and I hopefully will get enough American/etc country responses to not need to pay for more Turk samples from other countries.) Of course, if the results are ambiguous, I will simply collect more data, as I'm under no time limits or anything.

For the tertiary question, response rates to silvervine/etc, I am not sure that it is feasible to do surveys on them. There is not much mention of them online compared to catnip, and they can be hard to get. My best guess is that of the cat owners who have used catnip, <5% of them have ever tried anything else, in which case even if I get 200 responses, I'll only have 25 responses covering the others, which will give very imprecise estimates and not allow for any sort of modeling of response rates conditional on being catnip immune or factor analysis. If I'm right and the survey is unable to answer the question without recruiting thousands of cat owners, then that tells me I will have no choice but to continue experimenting myself and contact the local pound & animal rescue organizations asking if I can use my battery of substances on their sets of cats.

As for your question suggestions: weight/current-age/body-shape-fatness haven't been suggested in the catnip literature as moderators, current age seems like it should be irrelevant, and asking for a free response description of the catnip response is really burdensome on the user compared to multiple-choice or checkboxes (survey guidelines emphasize as few free-responses as possible, no more than 1 or 2) and the catnip response is pretty stereotypical even across species so there wouldn't be much point.

OK, no complaints so far, so I'm just going to launch it. Consider the survey now live. Did I mention that there will be cake?