Computer-based platforms/systems/devices/components and/or objects configured for generating values for data structures and methods of use thereof

A method comprising:

• training, by at least one processor, an instant structure generation model to generate a plurality of unique candidate file structures by:
• configuring the instant structure generation model to receive as input a candidate file structure that comprises a plurality of fields having a plurality of proposed values and return as output the plurality of unique candidate file structures with a plurality of proposed value variations, wherein the plurality of proposed values comprise at least one populated field having at least fixed value, and at least one other field populated with a respective combination of values of each combination of each value of the at least one other field;
• and
• inputting as training data, by the at least one processor, a plurality of accepted historical file structures into the instant structure generation model, wherein each accepted historical file structure comprises the plurality of fields having at least one historical value;
• receiving, by at least one processor, the candidate file structure;
• providing, by the at least one processor, the candidate file structure to the trained instant structure generation model;
• and
• receiving, by the at least one processor, the plurality of unique candidate file structures as output from the trained instant structure generation model.

A system comprising:

• at least one processor in communication with at least one computer readable storage medium having software instructions stored thereon, wherein the software instructions, when executed, cause the at least one processor to perform steps to:
• receive, by at least one processor, at least one proposed file structure, wherein the at least one proposed file structure comprises a plurality of fields, wherein at least one populated field of the plurality of fields is populated with at least one fixed value;
• input, by the at least one processor, the at least one proposed file structure into an instant structure generation model configured to:
• generate a plurality of candidate value variations by varying each value of at least one other field of the plurality of fields within a threshold value range of each field of the plurality of fields, the at least one other field being different from the at least one populated field;
• and
• generate a plurality of unique candidate file structures based on each combination of each value of the at least one other field while holding the at least one populated field as fixed;
• access, by the at least one processor, a plurality of accepted historical file structures, each accepted historical file structure comprising the plurality of fields having a plurality of accepted historical values;
• input, by the at least one processor, the plurality of unique candidate file structures and the plurality of accepted historical file structures into at least one structure similarity machine learning model to output a subset of unique candidate file structures based at least in part on:
• a similarity of the plurality of candidate value variations of each unique candidate file structure to the plurality of fields having a plurality of accepted historical values of each accepted historical file structure, and trained structure similarity machine learning model parameters;
• and
• display, by the at least one processor, a list of the subset of unique candidate file structures via a graphical user interface;
• wherein the graphical user interface comprises a one-click action element for each unique candidate file structure;
• wherein the one-click action element is configured to, upon a selection of the one-click action element for a particular unique candidate file structure, cause the at least one processor to generate a particular file based at least in part on the particular unique candidate file structure comprising the at least one populated field and the at least one other field of each associated candidate value variation.