Do We Really Need to Thank the Beatles for the Financing of the Development of the Computed Tomography Scanner?
Bibliographic record
Abstract
It is commonly believed that the revenues from the selling of the Beatles' records by Electric and Musical Industries (EMI) allowed the company to develop the computed tomography (CT) scanner. Some went to define this as the Beatles' gift to medicine. However, significant controversies and discrepancies arise from analysis of this statement, making its correctness doubtful. The details of financing required for the CT development and the part of EMI in financial input have never been publicly announced. This work analyzes the financial contributions to the CT development and investigates if the revenues received from the sales of the Beatles' records were used for the creation of the CT scanner. Timeline of the development of the EMI CT scanner and the financial inputs of EMI and British Department of Health and Social Security (DHSS) were assessed. Without salary expenses to Godfrey Hounsfield and his team, the development of the CT scanner cost EMI approximately £100,000. The British DHSS's expenses were £606,000. Hence, the financial contribution of DHSS into the development of the CT scanner was significantly bigger than that of EMI. Accordingly, British tax payers and officials of British DHSS are to be thanked for the CT scanner. The Beatles' input into the world's culture is valuable and does not require decoration by nonexistent connection to the development of CT. A positive aspect to this misconception is that it keeps in public memory the name of the company that developed the CT scanner.
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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 | 0.009 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.025 | 0.010 |
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".