Bibliographic record
Abstract
unless otherwise noted, is the intellectual property of The Mandt System, Inc.. All materials are copyrighted, and all rights are reserved. Copying, duplicating, selling, or otherwise reproducing, storing in a retrieval system, or transmitting in any form other, in whole or in part, except as provided herein or without the expressed written consent of The Mandt System, Inc, is a violation of the copyright laws of the United States, Canada, Australia, and the European Union. Brief quoting of the information with references consistent with APA standards in is permitted. Relationships – The Most Powerful Tool Relationship is the single most important therapeutic modality to ameliorate threats of violence and the need for restraint ” (Breggin, 1999) “The most powerful restraints on violent Behaviour is healthy human attachment. ” (Brendtro and Long, 1995) Focusing on environment, structure, early intervention, and patient relationships were pivotal, however, this team had to take programming to another level. It required understanding that for change to be meaningful, it would mean affecting culture. (Riemer, 2009)
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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.074 | 0.074 |
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".