Results: Fixed Stars Natal Interpretation #

Overview #

This 2026 analysis applies a continuous weighting system to the study of Fixed Stars. Instead of asking "Is Star X conjunct Planet Y?" (a binary yes/no), we calculate the Cosine Intensity of the alignment.

The formula $ \sum \cos(\theta_{diff}) $ allows us to quantify the total strength of a star's influence across a population, rewarding tighter orbs exponentially more than wide ones.

Data Source #

• Sample: ~936 Public Figures (Celebrities, Politicians, Scientists, etc.).
• Source: Migrated from Project 11 (celebrity_data.csv).
• Categories: Individuals are grouped by their "Cause" of fame/category (e.g., Cardiac-related, Accident, etc - Note: mapped from available metadata).

Key Findings (Visualized) #

1. Star-Planet Relationships (heatmap_star_planet.png) #

This heatmap reveals the aggregate intensity of specific Planet-Star pairs.

• X-Axis: Planets (Sun, Moon... Pluto, Nodes).
• Y-Axis: Fixed Stars (Algol, Sirius, etc.).
• Interpretation: Darker/Brighter cells indicate a higher cumulative "tightness" of conjunctions. This helps identify if, for instance, the Moon is more frequently tightly bound to specific fixed stars in this population than Jupiter is.

2. Category Affinity (heatmap_category_star.png) #

This visualization shows which stars have the strongest "pull" or intensity within specific professional or biographical categories.

• X-Axis: Fixed Stars.
• Y-Axis: Categories (derived from user data).
• Interpretation: If the "Politician" row has a bright spot under "Regulus", it suggests that Regulus features prominently and tightly in the charts of politicians in this dataset.

3. Orb Precision (star_orb_tightness.png) #

This chart displays the Average Cosine Similarity for contacts to each star.

• High Bar: Means that when this star is contacted, the aspect tends to be very exact (tight orb).
• Low Bar: Means the star attracts wider, looser aspects in this sample.
• Value: Values closer to 1.0 indicate higher precision. 0.999 is roughly a 2.5° orb.

Data Outputs #

• detailed_conjunctions.csv: The raw data containing every calculated conjunction with its specific cosine_similarity score.
• analysis_results.csv: (Legacy) Summary counts, superseded by the visual intensity maps.

Conclusion #

Moving to a cosine-weighted model removes the arbitrary nature of "orbs" and allows for a more nuanced view of stellar influence, highlighting "peaks" of intensity rather than just counts.

Statistical Interpretation #

The shift to a Cosine Similarity metric fundamentally changes the statistical landscape of this analysis from a discrete binomial distribution (Hit/Miss based on orb) to a continuous distribution of intensity.

1. Intensity vs. Frequency: In traditional analyses, a star might appear "less frequent" strictly due to arbitrary orb cutoffs. In this weighted model, a rare but extremely precise conjunction (e.g., 0.01° orb, score 0.9999) contributes significantly more to the signal than multiple loose conjunctions. This effectively reduces noise from "wide orb" hits that likely hold little astrological significance.

2. Category Clustering: The heatmaps allow us to assess "Mean Intensity" per category. A statistically significant finding in this context appears as a category cluster (e.g., "Politician") that is consistently brighter (higher mean cosine) for specific stars than the baseline population. If the distribution of intensity scores for "Politicians + Regulus" shifts significantly rightward compared to "Musicians + Regulus", it indicates a specific affinity.

3. Signal-to-Noise Ratio: By using the full cosine curve (peaking at 1.0), we implicitly weight the effective "power" of the aspect. This mimics the inverse-square law of physical forces, suggesting that astrological influence—if it exists—decays rapidly with distance, rather than remaining constant up to an arbitrary 2° wall. This method provides a more robust framework for detecting subtle signals in large datasets.

Here are the Top Significant Findings (Z-Score > 2.0 or < -2.0): #

Cancer Diagnosis & Altair (Z = -2.32):

Finding: Individuals in the "cancer" category have a significantly lower mean intensity connection to the star Altair than random chance. Interpretation: This implies an "avoidance" or lack of prominence of Altair in these charts.

Overdose & Regulus (Z = +2.26):

Finding: Individuals who died of "overdose" have a significantly higher mean intensity connection to Regulus ("The Heart of the Lion") than expected. Interpretation: This is a statistically significant positive association (P=0.030).

Homicide & Altair (Z = +2.07):

Finding: Individuals who died of "homicide" have a higher connection to Altair. Comparison: This is interesting because "Cancer" patients had a lower connection to the same star.