The Foundation of The Quarters Theory
Bibliographic record
Abstract
The Quarters Theory focuses on the 1000 Price Interest Points (PIPs) ranges between the Major Whole Numbers in currency exchange rates and divides these ranges into four equal parts, called Large Quarters. It offers universal, constant, and familiar price ranges that allow quick and precise price analysis of any currency pair. This chapter discusses the foundation of the Quarters Theory and presents an example of a price analysis of the exchange rates of three currency pairs using the methodology of The Quarters Theory. The Quarters Theory is based on the premise that the daily fluctuations of currency exchange rates are not random and that currency exchange rates fluctuate in an orderly manner between the Large Quarter Points within each 1000 PIP Range defined by two Major Whole Numbers. The Quarters Theory proposes that every significant price move in currency exchange rates takes place from one Large Quarter Point to another, in gradual increments of 250 PIPs, the range between two Large Quarter Points. The Quarters Theory organizes the daily fluctuations of currency exchange rates in a systematic arrangement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".