Coordination, Defense & Reproduction — Print · Life Science & Scientific Inquiry, Grade 7

1. Mean: (0.20 + 0.25 + 0.30) ÷ 3 = 0.75 ÷ 3 = 0.25 seconds.

2. Range: 0.30 − 0.20 = 0.10 seconds, which is a substantial spread relative to the mean across only three trials.

3. Describe the pathway: a stimulus detected by a receptor, carried by sensory neurons, processed, carried out by motor neurons to a muscle, which produces the response.

4. Correct the claim: the test measured the speed of that pathway on one task; intelligence involves reasoning and knowledge the test never engages.

The mean is 0.25 seconds, from (0.20 + 0.25 + 0.30) ÷ 3, and the range is 0.30 − 0.20 = 0.10 seconds. That range is worth noticing: a spread of 0.10 around a mean of 0.25 is large in proportion, and with only three trials the mean is not a stable estimate — practice, alertness and expectation can move it easily. What the test measured is a signal pathway: a stimulus detected by a receptor, a signal carried along sensory neurons to the central nervous system, processed there, and carried out along motor neurons to a muscle that produced the response. Each stage takes time, and the total is what the stopwatch recorded. The draft's claim does not follow. Intelligence, however it is defined, involves reasoning, knowledge, memory and judgement, none of which this task required and none of which a transmission speed could reveal. The measurement also has no control for the conditions that affect it — whether the person was expecting the signal, how many practice attempts they had, how alert they were, the temperature of the room. A defensible report would read: mean 0.25 seconds, range 0.10 seconds, over three trials of one stated task, under unstated conditions, which measures the speed of one response pathway and nothing about the person beyond it.

1. Identify the deviation: the quantity rose by 4 units, from 20 to 24, taking it above the stated range of 19 to 22.

2. Identify the direction of the response: the output lowered the quantity, opposing the rise, which is negative feedback.

3. Compare the final value with the range: 21 lies inside 19 to 22, so the loop returned the quantity to its working range.

4. State the limit: the units are invented and the range stipulated, so nothing here corresponds to a measured human quantity.

This is negative feedback. The quantity deviated upward by 4 units, from 20 to 24, which took it above the stated working range of 19 to 22. A detector sensed the value and activated an output, and that output lowered the quantity — a response in the opposite direction to the deviation, which is exactly what negative feedback means. The final value of 21 lies inside the working range, so the loop did its job: it did not return the quantity to its starting value of 20, and it was not required to, because regulation holds a quantity inside a band rather than at a point. All four parts of a loop are present in the record: a regulated quantity, a detector, an output acting as the effector, and a change in the quantity that the detector would sense on the next cycle. What the record cannot support is any medical reading. The units are not named, the range is stipulated rather than measured, and nothing identifies what is being regulated or in what. A model like this is built to make the structure of regulation visible, and its numbers are chosen so the arithmetic is clear. Reading them as clinical values would be a category error, and judgements about a real body need measured values, established ranges and expertise this course does not provide.

1. Identify the evidence for specificity: the model distinguishes A from B, so the recognition is matched to particular features rather than general.

2. Identify the evidence for memory: the response to A begins faster after repeated exposure, so something from the earlier encounters persists.

3. Separate faster from complete: a quicker response is not the same as preventing the outcome, and the model measures only timing.

4. Name a limit: symbols are not pathogens, one symbol is not a varied population, and nothing here corresponds to a person or a treatment.

The model demonstrates two things. Recognition is specific: Symbol B differs from A and is not treated as A, so the response is matched to particular features rather than triggered by anything foreign. And something persists: the response to A begins faster after repeated exposure, which means information from earlier encounters is retained and used — the model equivalent of immune memory. Both correspond to real features of the specific immune response, in which antibodies are shaped to match molecules on one pathogen's surface and cells persist after recovery to respond faster on a second encounter. What the model does not show is protection. It measures how quickly a response begins, and a faster response is not the same as one that prevents the outcome; the model contains no outcome at all. It also says nothing about Symbol B, which was never repeated, so no claim about a response to B is available either way. The limits worth stating are that symbols are not pathogens, a single fixed symbol is not a population of organisms that vary and change — which is exactly why colds recur while chickenpox usually does not — and no element of the model represents a person, a treatment or a health decision. The model is adequate for showing the shape of specific recognition with memory, and inadequate for anything beyond that.

1. Classify A: new individuals from parent tissue with no fusion is asexual reproduction, so the offspring begin as genetic copies of the parent.

2. Classify B: fusion of two gametes is sexual reproduction, producing a zygote with a combination of information from both parents.

3. Explain A's variation: a mutation is a change in genetic information arising independently of reproduction, so copies can come to differ even with no fusion involved.

4. Separate production from success: both counts say how many individuals were produced, not how many survived to reproduce themselves.

A reproduces asexually: new individuals come from parent tissue with no gametes fusing, so each begins with the same genetic information as its parent. B reproduces sexually: two gametes fuse at fertilisation to form a zygote carrying a combination of information from both parents, which is why B's offspring differ from each other and from either parent. The mutation in A's offspring is the interesting part, because it shows that asexual reproduction producing copies does not mean a population of copies forever. A mutation is a change in the genetic information itself, arising independently of how reproduction happened, and once it occurs it is passed to that individual's own offspring. So asexual populations do vary — they simply acquire variation slowly, one change at a time, instead of generating new combinations every generation the way sexual reproduction does. On the second question, neither record says anything about success. Producing offspring and reproducing successfully are different measures: what counts over a life cycle is how many offspring survive to reproduce themselves. A cod releasing millions of eggs and a bird raising two chicks can achieve the same outcome, and the records here give no survival data at all. To compare A and B you would need the number of offspring reaching reproductive age, across a stated period and set of conditions — and the answer would likely differ between a stable environment, which favours copies of a well-adapted parent, and a changing one, which favours variation.

1. Calculate A: 18 ÷ 20 = 0.9, which is 90 per cent germination within seven days.

2. Calculate B: 12 ÷ 20 = 0.6, which is 60 per cent germination within the same seven days.

3. State the difference precisely: 30 percentage points more seeds germinated under treatment A within the stated interval.

4. Qualify the claim: germination percentage over seven days says nothing about later growth, yield or survival, and twenty seeds per treatment is a small sample run once.

Treatment A germinated 18 of 20 seeds, which is 18 ÷ 20 = 90 per cent, and treatment B germinated 12 of 20, which is 12 ÷ 20 = 60 per cent. The difference is 30 percentage points more germination under A within the seven days recorded. Because the record states that species and all other conditions were matched and that water amount was the treatment, the comparison is structured to attribute the difference to water, which is more than most informal comparisons manage. Two things are still worth saying about what it measures. It is a total at one moment, not a rate: a tray that reaches 60 per cent by day seven might reach 90 by day ten, and the record cannot distinguish a treatment that prevents germination from one that merely delays it. And twenty seeds per treatment, run once, is a small sample, so ordinary variation in seed quality could account for part of a difference this size. What the record cannot address at all is anything after germination. A seed that germinates may still produce a weak seedling, and the water amount that favours germination is not necessarily the one that favours growth, flowering or yield — those are separate outcomes over longer periods, needing their own measurements. The supportable claim is narrow and useful: under these conditions, over seven days, treatment A was associated with 90 per cent germination against B's 60 per cent.