Bibliographic record
Abstract
has been studying schizophrenia for over 20 years and has thoughtfully assembled the field's current knowledge as to what schizophrenia is and is not.Early in the book, he makes an analogy to heart failure, observing that edema and shortness of breath characterize heart failure but that the causes can be many and varied and may not necessarily originate in the heart.So, too, the symptoms of schizophrenia can be variously looked on as brain failure-failure of the brain to synthesize the information it perceives, to appreciate it affectively, to distinguish between self-generated stimuli and stimuli coming from outside, or to create meaning out of perception and to remember it.Like the multiple causes of heart failure, there are probably a multitude of causes for brain failure and Dr Williamson leads the reader through the many possibilities.He strongly suggests setting aside the search for a single cause.Because the final result is brain failure, understanding how the brain works is essential to understanding schizophrenia.The author believes, and I believe he is right, that psychiatrists know too little about the brain.Despite advances in molecular genetics, neuropsychology, neurochemistry, and
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".