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Given the complex interplay between CYP450-mediated activation of CCl4 and downstream apoptotic signaling, how can the authors confidently attribute hepatoprotection to antioxidant action alone without assessing upstream pathways like CYP2E1 expression or caspase activation? Isn’t this a mechanistic oversimplification that limits the study’s interpretive depth?
1. Could you provide the exact annotation guideline given to the domain experts? Was the instruction strictly to label “nodes on the main stem” or more broadly to label “nodes”? If the former, this constitutes a systematic error in dataset construction for a general node detection task.
2. The high B-FP rates for nodes (e.g., 59% for YOLOv5x6) are a central part of the results discussion. How can we interpret the model’s true precision for node detection when a potentially large fraction of its correct predictions are considered errors by the evaluation protocol? Does this not render the reported precision and mAP values for the node class unreliable?
3. If the ultimate agricultural application requires counting only main stem nodes (e.g., for internode length estimation), was the model architecture or post-processing designed to filter predictions based on spatial context (e.g., proximity to a central stem line)? The paper currently presents a general object detector, not one constrained by this biological rule.