Geophysical Variables and Behavior: XCV. Annual January Rainfall May Modulate the Incidence of Luminous Phenomena within the San Francisco Basin
Bibliographic record
Abstract
The role of precipitation as a modulator of processes that influence the numbers of reports of anomalous luminous phenomena was investigated within the San Francisco Basin for the years 1950 through 1969. More than 50% of the variance in the numbers of these reports was accommodated by the amount of rainfall during the months of January. The relationship was strongest for events within 100 km of the city. Years in which January rainfall exceeded 8.5 in. and the numbers of earthquakes within the basin increased were associated with the largest numbers of general reports within 400 km from the city, particularly if the previous year had been drier and displayed less seismic activity. Application of the equation to years 1970 through 1995 predicted that above average (z score > 1.5) numbers of luminous displays should have occurred during the years 1973, 1993, and 1995. The results support the corollary of the tectonic strain theory that fluid injection or hydrological loads, natural or man-made, can affect the processes of tectonic strain which facilitate the creation of unusual luminous phenomena.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".