MétaCan
Menu
Back to cohort
Record W3176907948 · doi:10.33805/2572-6978.154

Application of IARTI and Ameliorating Principles to Improve Compliance and Completion of Treatment in General Dental Practice

2021· article· en· W3176907948 on OpenAlexaff
Louis Z.G. Touyz, Leonardo M. Nassani

Bibliographic record

VenueDental Research and Management · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsDental practiceAnxietyPaymentDistressModerationClinical PracticePsychologyMedicineNursingPsychotherapistBusinessDentistryPsychiatrySocial psychologyFinance

Abstract

fetched live from OpenAlex

Introduction: Many General Dental Practitioners run single handedly a mini-hospital. Practice administration, delivery of treatment and financial stewardship are all demanding with consequent induction of uncertainty, distress, and diminished performance, loss of satisfaction and unwelcome depression and anxiety. Aim: This contribution describes moderation of stresses in general dental practice by applying amelioration policies. Discussion: This advisory is targeted at all dentists involved in extensive dental therapy. The stress and anxiety of practice management is improved by applying newly established principles of practice, namely the Initial Assessment and Ranking of Treatment Index (IARTI) and What arrangements Have you made to meet your Oligations (WAHUM TOMYO), Immediate Payment Therapy (IPP) and Big Toe Philosophy (BTP). Conclusion: By applying these fundamental principles into general dental practice, much anxiety is relieved, challenges and problems are avoided or resolved and successful practice of dentistry is realized. A much higher frequency of failures will occur if these principles are not applied. Success does depend on applying IARTI and WAHUM TOMYO, IPP and BTP.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.212
GPT teacher head0.541
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDental Research and ManagementSame topicMedical Malpractice and Liability IssuesFrench-language works237,207