Challenge ideal doubling in a conceptual amplification record
Polymerase chain reaction conceptually repeats strand separation, primer recognition and polymerase extension to increase a selected DNA target. Primer specificity defines which sequence is preferentially amplified. The lesson describes this mechanism without supplying primers, reaction composition, operating temperatures or a physical procedure.
Learning outcome: Compare efficiencies 1 and 0.8 at ten and twenty cycles. Retain the ratio to ideal doubling and identify where the formula’s fixed-efficiency assumption would need empirical validation. State separate roles for negative and positive controls.
Starting recap
Trace strand direction, processing and molecular accounting; distinguish synthesis from abundance, local from shared regulation, and conditional assay evidence from identity or function claims.
All lessons are open directly. Your saved experiments remain when you leave and return.
Try
Starting with ten target copies, ten ideal cycles give 10×2¹⁰=10240. At efficiency 0.8, ten cycles give 10×1.8¹⁰≈3570.47, only about 0.34868 of the ideal reference. The difference occurs without changing the assigned initial amount.
Open the experimentPredict
Does a lower endpoint necessarily mean fewer starting copies if amplification efficiency is unknown?
Experiment
Compare efficiencies 1 and 0.8 at ten and twenty cycles. Retain the ratio to ideal doubling and identify where the formula’s fixed-efficiency assumption would need empirical validation. State separate roles for negative and positive controls.
Test an exponential amplification assumption against efficiency
Worked teaching model · synthetic values · Purely conceptual fixed-efficiency model starting with10 target copies: N=10(1+e)^cycles. No primer sequence, reaction recipe, temperatures or physical experiment. Finite reagents, inhibition, stochastic early cycles and plateau omitted; copy estimates are not diagnosis.
Reset keeps your prediction, captures and practice history.
Small efficiency differences compound over repeated cycles before any plateau.
Denaturation, primer recognition and polymerase extension explain conceptual amplification. The model provides no actionable procedure. A negative/no-template control tests contamination; an appropriate positive control tests assay failure. Amplification alone does not prove target identity or original abundance.
Solid: Selected efficiency. Dashed: Ideal doubling. Axes rescale to the current range; use labeled values rather than comparing graph heights across settings.
| Virtual cycles | Selected efficiency (Model copy count) | Ideal doubling (Model copy count) |
|---|---|---|
| 0 | 10.00000 | 10.00000 |
| 1 | 18.00000 | 20.00000 |
| 2 | 32.40000 | 40.00000 |
| 3 | 58.32000 | 80.00000 |
| 4 | 104.9760 | 160.0000 |
| 5 | 188.9568 | 320.0000 |
| 6 | 340.1222 | 640.0000 |
| 7 | 612.2200 | 1280.000 |
| 8 | 1101.996 | 2560.000 |
| 9 | 1983.593 | 5120.000 |
| 10 | 3570.467 | 10240.00 |
| Quantity | Value | Unit |
|---|---|---|
| Model target copies after selected cycles | 3570.467 | copies |
| Ideal doubling reference | 10240 | copies |
| Fraction of ideal doubling reference | 0.3486784 | ratio |
Retain prior predictions, settings and quantities in the notebook. These are original supplied/calculated comparisons, not physical specimen observations or laboratory participation.
Small efficiency differences compound over repeated cycles before any plateau.
Denaturation, primer recognition and polymerase extension explain conceptual amplification. The model provides no actionable procedure. A negative/no-template control tests contamination; an appropriate positive control tests assay failure. Amplification alone does not prove target identity or original abundance.
Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.
Understand
Apply
Public practice checks a specific claim. It does not establish independent mastery.
An ideal virtual packet begins with five copies and undergoes eight doubling cycles. Find the final model count; explain why this alone cannot certify target identity.
Continue
Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.
Skipping retains experiments and awards no mastery.
Save a science backup or import one
Science work is stored locally in this browser, separately from mathematics and AI. It does not sync automatically. Use this science-only backup; this checkout's older all-subject export does not include science.
A legacy file is available only when the complete snapshot fits the 36 MB limit. For larger snapshots, prepare a complete file set below; never discard notebooks to make a smaller file.
Matching imported notebook drafts replace their current drafts. Omitted lessons and known first attempts remain. Export your current work first if you want to retain both drafts.
Complete file sets and course backups
A file set can hold more work than one science file. Keep its manifest and every part together. Each file is limited to 36 MB. This format needs this version of LearnAI or a compatible newer version; older versions can use only the legacy single-file backup above.
The set includes every saved science course and global continuation at this moment. Later edits need a new export. A conflicting tab exports its own visible work, which may differ from saved work in another tab.
0 file(s) selected. File order and filenames do not determine identity. Missing, changed or conflicting parts block the entire restore; no good part is applied by itself.
Science storage: loading. No account or remote computation is required.