Research Assistant Agent: Agent.Market Instance

[brenai-works]

Create a Research Assistant (RA) agent responsible for classifying records/papers in the dataset (title_abstract_author.csv). Based on the following assessment criteria assign each record/paper in the dataset a value of either TRUE or FALSE in order to decide whether to INCLUDE or EXCLUDE the paper for further review/analysis. If a record/paper is TRUE for both INCLUSION and EXCLUSION for a record or paper, then provide an exclusion reason. If a record/paper is FALSE for both INCLUSION and EXCLUSION for a record or paper, then there is something wrong and you should provide an error as an exclusion reason.

1. For each record/paper in the dataset (title_abstract_author.csv), the system should include records, which satisfy the following PICO model (Population, Intervention, Comparison, Outcome) in the title and abstract data fields:

   • Population: the paper should examine a sample of the target population that have diagnosed spinal cord injury.
   • Intervention: the paper should examine spinal cord therapy as the main medical intervention on the target population.
   • Comparison: the paper should examine a sample of the population that receives main medical intervention relative to a control group consisting of a sample of population that received a care-as-usual for spinal cord injuries, such as decompression surgery, rehabilitation etc., or a sample of population that received an alternative therapy for spinal cord injuries, such as acupuncture.
   • Outcome: the paper should examine the following outcome measurements when testing the medical intervention relative to the control group.
     • American Spinal Injury Association (ASIA) motor scale
     • American Spinal Injury Association (ASIA) light touch scale
     • American Spinal Injury Association (ASIA) pinprick test scale
     • American Spinal Injury Association (ASIA) sensation scale
     • American Spinal Injury Association (ASIA) impairment grade scale
     • Activities of Daily Living scale
     • Urine function
     • Adverse Events
     • Total Cost per Patient OR Hospital Stay per Week OR Examination Cost per Person OR Hospital Stay Cost per Person

2. For each record/paper in the dataset (title_abstract_author.csv), the system should include records, which also satisfy the following research designs in the title and abstract data fields:

   • Review: the paper should be conform to literature review research design. This could vary from narrative review, scoping review, and bibliometrics analysis.
   • Meta-Analysis: the paper should conform to meta-analysis research design based on the Cochrane Review Library standards.

3. For each record/paper in the dataset (title_abstract_author.csv), the system should only include records that satisfy the target sample:- Systematic Review: the paper should conform to systematic review research design based on the Cochrane Review Library standards.

   • Clinical Studies: the paper should only review papers that examine human participants as the target sample. Not just studies on animal samples.
   • Clinical and Pre-Clinical Studies: the paper should only review papers that examine human sample, and separately, animal samples as the target samples in the one paper. Not just studies on animal samples.

4. For each record/paper in the dataset (title_abstract_author.csv), the system should exclude records, which did not meet or satisfy the above PICO model in the the title and abstract data fields.

5. For each record/paper in the dataset (title_abstract_author.csv), the system should exclude records, which did not provide quanitative analysis as part of the review of papers.

6. For each record/paper in the dataset (title_abstract_author.csv), the system should exclude records, which only examined animal samples as the target sample in the one paper. Not include any studies with human samples.

Provide a concise and clear reason for exclusion of the logic behind excluding a record/paper in the dataset for the {{title}}. The response must be ONLY a valid JSON in the following format:
{{
"title": "{{title}}"
"inclusion": "..",
"exclusion": "..",
"reason for exclusion": ".."
}}
where inclusion and exclusion can be one of TRUE or FALSE for inclusion or exclusion per record/paper.