{"id":"W4409210805","doi":"10.3390/computers14040135","title":"Enhancing Cryptographic Solutions for Resource-Constrained RFID Assistive Devices: Implementing a Resource-Efficient Field Montgomery Multiplier","year":2025,"lang":"en","type":"article","venue":"Computers","topic":"RFID technology advancements","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"King Salman Center for Disability Research","keywords":"Multiplier (economics); Cryptography; Computer science; Resource (disambiguation); Cryptographic primitive; Field (mathematics); Embedded system; Cryptographic protocol; Distributed computing; Computer security; Computer network; Mathematics; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003059334,0.0002401075,0.0002625225,0.0005033809,0.0004293729,0.00004557447,0.0003231702,0.0001427193,0.00001082726],"category_scores_gemma":[0.0001030501,0.0002773688,0.0001448964,0.0005765907,0.000081717,0.00005806771,0.0002225357,0.000253952,0.000004518744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001214173,"about_ca_system_score_gemma":0.00002468195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005491482,"about_ca_topic_score_gemma":0.00004306831,"domain_scores_codex":[0.9982882,0.00002516663,0.0004293745,0.0003742491,0.0001155555,0.0007674943],"domain_scores_gemma":[0.9988713,0.0005704911,0.00007279179,0.0003719947,0.0000527287,0.00006075157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001841757,0.0003922152,0.00977918,0.001465741,0.002698399,0.00003819486,0.002252522,0.5844157,0.04685379,0.02477014,0.04308251,0.2840675],"study_design_scores_gemma":[0.003180845,0.000156213,0.005380702,0.0009576165,0.0001871463,0.000006752241,0.001882059,0.793548,0.01509217,0.0007429988,0.1779386,0.0009268755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08152334,0.0004360528,0.9135934,0.0003848025,0.0004715365,0.0006235996,0.00002188924,0.0008392573,0.00210618],"genre_scores_gemma":[0.952756,0.000005749463,0.04628465,0.0005359731,0.00006634304,0.0002273326,0.00003132309,0.00003536614,0.00005727344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8712326,"threshold_uncertainty_score":0.9999679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056824389337837,"score_gpt":0.2442380316989094,"score_spread":0.233669787805531,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}