{"id":"W4388386139","doi":"10.30880/ijie.2021.13.02.003","title":"Development of a Lock Biometric Authentication System for a Battery Powered Locking Device","year":2021,"lang":"en","type":"article","venue":"International Journal of Integrated Engineering","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Reach Technologies (Canada)","funders":"Universiti Tun Hussein Onn Malaysia","keywords":"Fingerprint (computing); Biometrics; Fingerprint recognition; Lock (firearm); Battery (electricity); Actuator; Authentication (law); Computer hardware; Arduino; Computer science; DC motor; Embedded system; Engineering; Power (physics); Electrical engineering; Artificial intelligence; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004058706,0.000325091,0.0004875043,0.0005521477,0.0003453228,0.0005868451,0.0009245693,0.0006294961,0.004178774],"category_scores_gemma":[0.0006270422,0.0002592067,0.0002750265,0.0002550753,0.0002258345,0.001002822,0.0006544489,0.0004429545,0.002537262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001994226,"about_ca_system_score_gemma":0.0004252803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000267262,"about_ca_topic_score_gemma":0.000192508,"domain_scores_codex":[0.9995556,0.00004748605,0.00003927122,0.00009238287,0.0002256431,0.00003943695],"domain_scores_gemma":[0.9996449,0.00004710549,0.0000350831,0.00005805014,0.0001767926,0.00003802961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002908115,0.0001205423,0.002917774,0.0003619631,0.00003309464,0.0006396414,0.0002680892,0.0009895695,0.7536657,0.004295906,0.002918951,0.2334981],"study_design_scores_gemma":[0.0001456766,0.002227597,0.009924248,0.0001289486,0.0001381557,0.006284445,0.0001738015,0.0536925,0.8225914,0.001011418,0.1034987,0.0001830691],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1009187,0.0009551223,0.8817625,0.000392937,0.0005056254,0.0005834692,0.0002270375,0.006096808,0.008557777],"genre_scores_gemma":[0.6161423,0.000691599,0.355439,0.0003599031,0.0001194939,0.0005349418,0.0003973554,0.0002101265,0.02610527],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004178774,"threshold_uncertainty_score":0.01397938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204256891592968,"score_gpt":0.2288914371050527,"score_spread":0.216848868189123,"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."}}