Bibliographic record
Abstract
Addictions Clinical Textbook of Addictive Disorders Richard Frances, Sheldon Miller, Avram Mack, editors. New York (NY): The Guilford Press; 2005. 684 p. US$75.00. Reviewer rating: Excellent The Clinical Textbook of Addictive Disorders is must reading, not only for addiction clinicians but also for any mental health professional. The third edition of this book, published in 2005 by The Guilford Press, is revised and updated, with a few new chapters presenting recent advances in the field. The editors of this review are well-known in the community of addiction psychiatrists. Richard Frances and Sheldon Miller are among the founders of the American Academy of Addiction Psychiatry, with years of clinical, teaching, and publishing experience; Avram Mack has a special interest in addictive disorders and has published on addictions before. The contributors to this volume include writers such as Marsha Linehan, Edward Khantzian, and Judith Beck, none of whom require additional introduction. The book is intended to be a review. It consists of 28 chapters, which are organized into 5 sections. Practically all areas of addiction medicine are covered. Despite the fact that most chapters are concise and focused, they are able to convey advances in the field and cite many recent studies. It is convenient for readers with not much time that each chapter is basically a separate entity and does not require reading of the entire book to be fully understood. Most of the chapters have a brief conclusion or summary, and all contain an extensive list of references for those who wish to further their knowledge. The first section (Chapters 1 and 2), Foundations of Addiction, attempts to present a simple neurobiological model of addictions and gives a very interestingly written historical overview of substance use, misuse, and approaches to treatment within a social and cultural context. In Part II (Chapters 3 and 4) the reader finds a modern perspective on the assessment of addictive disorders. Chapter 3 describes a currently recommended psychological assessment procedure that consists of 3 stages and mentions the most frequently used scales and diagnostic tools. Chapter 4 provides an excellent overview of the newest biological and laboratory methods for the testing of different addictive disorders. This particular chapter can be very helpful to emergency physicians. The next section, Part III (Chapters 5 to 10), gives a detailed description of specific disorders related to the use of all groups of substances, including alcohol, tobacco, opioids, marijuana, hallucinogens, club drugs, and stimulants. …
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.119 | 0.100 |
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".