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           Figure 5. Validation on probability space. Three probability hyperplanes, 25%, 50%, and 75%, were illustrated based on Figure 3B. (A)
           Validation point selected at 20 w/v% concentration, 30°C nozzle temperature, and 0.4 mm path height. (A-1) Microscopic image evaluating
           the filament width. (A-2) Printing cube structure (5 × 5 × 5 mm ). (A-3) Top view of the printed grid structure (5 × 5 × 5 mm ). (B) Validation
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           point at 25 w/v% concentration, 29°C nozzle temperature, and 0.32 mm path height. (B-1) Microscopic image evaluating the filament width
           index. (B-2) Printing cube structure (5 × 5 × 5 mm ) with top view and side view. (B-3) Printing pyramid structure (10 mm × 10 mm × 8 mm)
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           with top and side view. Scale bar for (A-1) and (B-1) is 1.87 mm and 2 mm for the rest.
           of a scaffold is a critical information in supervised ML.   creates the continuity between bioprinters and can
           This problem raises the importance of a standardized   be used to eliminate the need for mass testing when
           metric for printability within the bioprinting community.   optimizing the bioprinting of new bioinks.
           With a standard evaluation method, ML models could be
           more generalized and applied across different materials,   Acknowledgments
           printers, and applications. This expansion would greatly   We acknowledge the financial support from SunP Biotech
           increase the usefulness of ML in bioprinting and allow for   company research grant (Drexel University–260676).
           high fidelity prints using new materials without the labor-
           intensive testing required to continuously build new ML   Conflicts of interest
           models.
                                                               We declaration no conflict of interest.
           5. Conclusions

           In this paper, the effects of path height, nozzle temperature,   Author contributions
           nozzle  gauge, and composition on printability  were   Z.F. conceptualized  the study, wrote the ML section,
           determined for PL 127 inks. Path height was shown to   performed SVM and visualization, reviewed and edited
           have an significant impact on printability, while nozzle   the  manuscript.  V.A. conducted  experiments,  wrote
           temperature  and  composition  affect  the  rheological   the  sections related  to evaluation  printing  parameters
           properties  of  PL  127,  and  thus,  affect  the  printability.   on print outcome, reviewed and edited the manuscript.
           Nozzle  gauge  alone  was  shown  to  have  no  effect.   W.S. conceptualized the study, reviewed, and edited the
           Rheological  data  and an investigation  into how these   manuscript
           parameters affect printability revealed the importance of
           viscosity in optimizing parameters and their interactions.  References
               Based on 12 UD training data, a ML model was
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