[262] Family: Pongidae
Order: Primata
Class: Mammalia
Phylum: Chordata
Kingdom: Animalia
SECOND SPECIES:
Species: Homo sapiens
Genus: Homo
Family: Hominidae
Order: Primata
Class: Mammalia
Phylum: Chordata
Kingdom: Animalia
Overall Genetic Match: 98.4%
“Believe it or not,” said Kawakita, “the identification of these two species was made solely on the genes. I didn’t tell the computer what these two organisms were. That’s a good way to show unbelievers that the Extrapolator isn’t just a gimmick or a kludge. Anyway, now we get a description of the intermediate species. In this case, as you said, the Missing Link.”
Intermediate form morphological characteristics:
Gracile
Brain capacity: 750cc
Bipedal, erect posture
Opposable thumb
Loss of opposability in toes
Below average sexual dimorphism
Weight, male, full grown: 55 kg
[263] Weight, female, full grown: 45 kg
Gestation period: eight months
Aggressiveness: low to moderate
Estrus cycle in female: suppressed
The list went on and on, growing more and more obscure. Under “osteology,” Margo could make out almost nothing.
Atavistic parietal foramina process
Greatly reduced iliac crest
10-12 thoracic vertebrae
Partially rotated greater trochanter
Prominent rim of orbit
Atavistic frontal process with prominent zygomatic process
That must mean beetle browed, thought Margo to herself.
Diurnal
Partially or serially monogamous
Lives in cooperative social groups
“Come on. How can your program tell something like this?” Margo asked, pointing to monogamous.
“Hormones,” said Kawakita. “There’s a gene that codes for a hormone seen in monogamous mammal species, but not in promiscuous species. In humans, this hormone has something to do with pair bonding. It isn’t present in chimps, who are notoriously promiscuous animals. And the fact that the female’s estrus cycle is suppressed—you also see that only in relatively monogamous species. The program uses a whole arsenal of tools—subtle AI algorithms, fuzzy logic—to interpret [264] the effect of whole suites of genes on the behavior and look of a proposed organism.”
“AI algorithms? Fuzzy logic? You’re losing me,” Margo said.
“Well, it really doesn’t matter. You don’t need to know all the secrets, anyway. What it boils down to is making the program think more like a person than a normal computer would. It makes educated guesses, uses intuition. That one trait, ‘cooperative,’ for example, is extrapolated from the presence or absence of some eighty different genes.”
“That’s all?” Margo said jokingly.
“No,” Kawakita replied. “You can also use the program to guess at a singleorganism’s size, shape, and behavior by entering the DNA for one creature instead of two, and disabling the extrapolation logic. And assuming the funding holds up, I plan to add two other modules for this program. The first will extrapolate back in time from a single species, and the second will extrapolate forward. In other words, we’ll be able to learn more about extinct creatures of the past, and guess at beings of the future.” He grinned. “Not bad, huh?”
“It’s amazing,” said Margo. She feared her own research project seemed puny by comparison. “How did you develop it?”
Kawakita hesitated, staring at her a little suspiciously. “When I first started working with Frock, he told me he was frustrated by the spottiness of the fossil record. He said he wanted to fill in the gaps, learn what the intermediate forms were. So I wrote this program. He gave me most of the rule tables. We started testing it with various species. Chimps and humans, as well as various bacteria for which we had a lot of genetic data. Then an incredible thing happened. Frock, the old devil, was expecting it, but I wasn’t. We compared the domesticated dog with the hyena, and what we got was not a smoothly intermediate species, but a bizarre life form, totally different from either dog or hyena. This happened with a [265] couple of other species pairs, too. You know what Frock said to that?”
Margo shook her head.
“He just smiled and said, ‘Now you see the true value of this program.’ ” Kawakita shrugged. “You see, my program vindicated Frock’s theory of the Callisto Effect by showing that small changes in DNA can sometimes produce extreme changes in an organism. I was a little miffed, but that’s the way Frock works.”
“No wonder Frock was so anxious that I use this program,” Margo said. “This can revolutionize the study of evolution.”
“Yeah, except nobody is paying any attention to it,” said Kawakita bitterly. “Anything connected with Frock these days is like the kiss of death. It’s really frustrating to pour your heart and soul into something, and then just get ignored by the scientific community. You know, Margo, between you and me, I’m thinking of dumping Frock as an adviser and joining Cuthbert’s group. I think I’d be able to carry much of my work over with me. You might want to consider it yourself.”
“Thanks, but I’ll stick with Frock,” Margo said, offended. “I wouldn’t have even gone into genetics if it weren’t for him. I owe him a lot.”
“Suit yourself,” said Kawakita. “But then, you might not even stay at the Museum, right? At least, that’s what Bill Smithback tells me. But I’ve invested everything in this place. My philosophy is, you don’t owe anyone but yourself. Look around the Museum: look at Wright, Cuthbert, the whole lot. Are they out for anyone but themselves? We’re scientists, you and I. We knowabout survival of the fittest and ‘nature red in tooth and claw.’ And survival applies to scientists, too.”
Margo looked at Kawakita’s glittering eyes. He was right in a way. But at the same time, Margo felt that human beings, having figured out the brutal laws of nature, could perhaps transcend some of them.
[266] She changed the subject. “So the G.S.E. works the same way with plant DNA as with animal DNA?” “Exactly the same,” Kawakita replied, returning to his businesslike manner. “You run the DNA sequencer on two plant species, and then download the data into the Extrapolator. It’ll tell you how closely the plants are related, and then describe the intermediate form. Don’t be surprised if the program asks questions or makes comments. I added a lot of little bells and whistles here and there while I was developing my artificial intelligence chops.”
“I think I’ve got the idea,” said Margo. “Thanks. You’ve done some amazing work.”