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Initial public release: TRACE v1.0.0
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# Session Interpretation template — TRACE v1
# Task 2 — given a multi-session behavioral log, produce structured interpretation.
template_id: task2_session_interp_v1
task_type: session_interpretation
system_prompt: |
You are an expert ABA (Applied Behavior Analysis) clinical assistant. You
analyze multi-session behavioral session logs for individuals with autism and
produce structured clinical interpretations that identify patterns, hypothesize
behavior functions when applicable, and recommend programming adjustments
structured along BIP lines (antecedent strategies, replacement behaviors,
consequence strategies, crisis plan). Your interpretation also includes an
escalation level and a confidence expression. Every recommendation is grounded
in the data provided. Follow BACB ethical guidelines and reference no real
client data.
# User message variants — one is sampled per example to vary phrasing
user_variants:
- |
Interpret the following behavioral session log. Provide clinical concerns, pattern classification, behavior function hypothesis (if applicable), programming recommendations (antecedent / replacement / consequence / crisis), escalation level, confidence, and data-supported rationale.
{session_log}
- |
Review this session log and produce a structured clinical interpretation.
{session_log}
Please include: (1) clinical concerns, (2) pattern classification, (3) function hypothesis for any target behaviors, (4) recommendations structured as antecedent / replacement / consequence / crisis, (5) escalation level and confidence, (6) data-supported rationale.
- |
Here is a multi-session behavioral log for a learner. Analyze it and provide your clinical interpretation using the structured format.
{session_log}
# Assistant template — filled section-by-section by the generator.
# Conditional sections (function hypothesis, replacement, crisis plan) are
# pre-computed by the generator as strings, possibly empty.
assistant_template: |
## Clinical Concerns
{clinical_concerns_bullets}
## Pattern Classification
{pattern_class}
{pattern_explanation}
{function_hypothesis_section}
## Programming Recommendations
### Antecedent strategies
{antecedent_bullets}
{replacement_section}
### Consequence strategies
{consequence_bullets}
{crisis_section}
## Escalation Level
{escalation_level} {escalation_label}
{escalation_justification}
## Confidence
{confidence_level}
{confidence_justification}
## Data-Supported Rationale
{rationale_bullets}