MLCR-AA: Medical Long Context Reasoning Benchmark
MLCR-AA Pass Rate
MLCR-AA Completeness
MLCR-AA Accuracy
Puntuación
MLCR-AA: puntuación
MLCR-AA: Puntuación vs. costo por tarea
Integridad de Medical Long Context Reasoning (MLCR-AA)
Uso de tokens
MLCR-AA: tokens de salida por tarea
Costo
MLCR-AA: costo por tarea
Velocidad
MLCR-AA: tiempo por tarea
Puntuación vs. fecha de lanzamiento
MLCR-AA: puntuación vs. fecha de lanzamiento
Tareas de ejemplo
Preguntas frecuentes
MLCR-AA es la evaluación de Artificial Analysis de MLCR, un benchmark abierto de Wisedocs que mide si los modelos de IA pueden razonar sobre historiales médicos largos y fragmentados como lo hacen los profesionales de siniestros al revisar casos de seguros y salud. Cada caso es un historial médico sintético de entre 25.000 y 64.000 tokens aproximadamente. Las preguntas abarcan seis niveles de dificultad, desde localizar un único dato hasta la síntesis clínica de nivel experto y el razonamiento compuesto de varias partes; MLCR-AA usa los dos más difíciles.
Un panel de tres jueces LLM contrasta cada respuesta con una verdad de referencia anotada por expertos y con el expediente médico original; las respuestas vacías no se evalúan y cuentan como no aprobadas. La puntuación principal es la tasa de aprobación: una respuesta aprueba cuando al menos dos de los tres jueces la consideran completa y sin afirmaciones que contradigan el expediente. Informamos la tasa de aprobación, junto con la exactitud y la completitud, sobre los conjuntos de preguntas expertas y compuestas de varias partes (difíciles).
Claude Sonnet 5.5 (Max, Default Fallback) tiene la puntuación MLCR-AA más alta, con una tasa de aprobación del 41,7 %. Ver modelo
Los profesionales de siniestros que revisan un historial de cientos de visitas reconstruyen la cronología, la causalidad, los patrones de tratamiento y la relevancia del siniestro a través de documentos fragmentados. MLCR-AA evalúa esa tarea con casos reservados, por lo que es relevante para las organizaciones que usan modelos comerciales para revisar historiales médicos, siniestros de seguros y otros trabajos sanitarios con documentos extensos.
No. MLCR-AA es una evaluación independiente y no contribuye al Artificial Analysis Intelligence Index.
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