Bibliographic record
Abstract
Abstract Complex analysis of a single variable is a type of mathematical analysis that observe properties for holomorphic functions. Over decades of development, complex analysis nowadays has played a more and more important role in algebraic geometry, fluid dynamics, quantum mechanics, and so on. This paper is to elaborate the Brannan’s coefficient conjecture, which was first proposed by D.A Brannan, J.G. Clunie, and W.E Kirwam in their paper on the coefficient problem for functions of bounded boundary rotation in 1973. The purpose of this paper is to give a detailed review and exploration of complicated but elegant proofs by D. Aharonov and S. Friedland. This paper mainly focuses on proving the inequality <?CDATA $\frac{{(1+\alpha x)}^{n}}{{(1-\text{x})}^{\text{p}}}\le \frac{{(1+x)}^{n}}{{(1-\text{x})}^{\text{p}}}$?> ( 1 + α x ) n ( 1 − x ) p ≤ ( 1 + x ) n ( 1 − x ) p for p > 0 |α| = 1 within condition n ≥ 1, which was derived from Brannan’s coefficient conjecture. The proof of the inequality is done by dividing the techniques of complex numbers, trigonometric functions, binomial expansions, and other mathematical formulas into three different cases.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".