{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004054397,0.0001801057,0.000322274,0.001052872,0.00002002395,0.0000596231,0.0003229089,0.00008904349,0.00001393448],"category_scores_gemma":[0.0002468963,0.000176252,0.0001532413,0.0006660096,0.000007669911,0.0001767449,0.00002403311,0.0001801155,0.000006032894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007498308,"about_ca_system_score_gemma":0.0002018602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002679789,"about_ca_topic_score_gemma":0.000002690935,"domain_scores_codex":[0.9983156,0.00001534248,0.0009308422,0.0001123536,0.0004373481,0.0001884616],"domain_scores_gemma":[0.9979888,0.0001344571,0.0002477885,0.0001167422,0.001436392,0.00007587303],"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":[0.00004595872,0.00006235798,0.0002778242,0.0007948423,0.00138929,0.00008197383,0.0009945338,0.1339567,0.8539276,0.0003672545,0.000245669,0.00785608],"study_design_scores_gemma":[0.001359456,0.00004265273,0.000864477,0.003025505,0.0000736917,0.0006184286,0.001511979,0.2572806,0.7115452,0.000004969313,0.02329262,0.000380404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4592037,0.0006767077,0.5359811,0.00003552985,0.003807033,0.00009704406,0.00003231488,0.00008392807,0.00008264087],"genre_scores_gemma":[0.9635044,0.00000992681,0.03615646,0.000005419408,0.0002095648,0.00001113862,0.00003939547,0.00004481618,0.00001891802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5043007,"threshold_uncertainty_score":0.7187347,"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."}}