Bibliographic record
Abstract
Based on a new rigorous ensemble approach to quantum mechanics, and without stressing any idea or concept of reality, the entire EinsteinPodolskyRosen (EPR) problem can be boiled down to the question of whether the separability principle of the natural sciences is universally valid. To give a precise answer first of all Bell's inequality is deduced from said ensemble point of view and with minimal requirements only. (In the final discussion of the results it turns out that Bell's inequality defines the upper bound for those basic correlations that are due to a mere conservation law.) Then, by use of Wheeler's gedanken experiment with coin halves, I show that the statistical operator representing an ensemble under investigation may be either separable (in a simplified sense) or not. The conceptual consequences of nonseparability are explained, and a general EPR-type experiment is re-examined. Thereby, it is proven that, if and only if, the statistical operator is nonseparable, Bell's inequality may be violated. Experimental evidence demands nonseparable operators. So, if quantum mechanics is assumed to make statistical statements on the results of measurements on ensembles only, there is no way to avoid acceptance of its (operationally) holistic character, and the question posed at the outset must be negated. PACS Nos : 03.65.Ta, 03.65.Ud
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.005 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".