Bibliographic record
Abstract
THE MULTIPLE ETIOLOGIES OF SCHIZOPHRENIA PROMPT US TO RAISE THE QUESTION: what final common pathway can induce a convincing sense of the reality of the hallucinations in this disease? The observation that artificial stimulation of an intermediate order of neurons of a normal nervous system induces hallucinations indicates that the lateral entry of activity (not resulting from canonical synaptic transmission) at intermediate neuronal orders may provide a mechanism for hallucinations. Meaningful hallucinations can be de-constructed into an organized temporal sequence of internal sensations of associatively learned items that occur in the absence of any external stimuli. We hypothesize that these hallucinations are autonomously generated by the re-activation of pathological non-specific functional LINKs formed between the postsynaptic membranes at certain neuronal orders and are examined as a final common mechanism capable of explaining most of the features of the disease. Reversible and stabilizable hemi-fusion between simultaneously activated adjacent postsynaptic membranes is viewed as one of the normal mechanisms for functional LINK formation and is dependent on lipid membrane composition. Methods of removing the proteins that may traverse the non-specifically hemi-fused membrane segments and attempts to replace the phospholipid side chains to convert the membrane composition to a near-normal state may offer therapeutic opportunities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".