Bibliographic record
Abstract
Tumor marker studies were conducted measuring 2,277 malignancies using a cut-off of 3 fmol/ml. As found 110 of 110 trophoblastic malignancies or 100% were positive for ß-core fragment an hCG serum degradation product. Just 949 of 2167 (44%) of non-trophoblastic or other cancers were positive using this 3 fmol/ml cut-off. When the cut-off of the assay was lowered to 0.1 fmol/ml, or lowered by 30-fold 100% of non-trophoblastic or other cancers were detected, or all cancers were detected. What do cancers secrete. Cancer were tested with three immunoassays, Immulite total hCG, B152 hyperglycosylated hCG and FBT11 free ß-subunit, serum of 34 trophoblastic cancers and 32 non-trophoblastic cancers were tested. A total of 34 of 34 trophoblastic cancer produced primarily hyperglycosylated hCG (B152 hyperglycosylated assay 96%±12% of Immulite), and 32 of 32 non-trophoblastic cancers produced primarily hyperglycosylated hCG free ß-subunit (B152 hyperglycosylated assay 102%±6.2% of Immulite, FBT11 free ß-subunit assay 128%±10% of Immulite). Seven independent laboratories each showed with a wide mixture of cancers (patient tissue and cancer cell lines) that ß-subunit promoted malignancy (cell growth, cell invasion and blockage of apoptosis) in cancer cells. I then showed that hyperglycosylated hCG and its ß-subunit promoted malignancy in 10 different cancer cell lines. I then tied my data and the seven independent laboratory data together and concluded that hyperglycosylated hCG and its ß-subunit drove malignancy in all or most cancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".