{"id":"W4255926796","doi":"10.36227/techrxiv.12061632","title":"Smart Raspberry Pi Bank Safety Deposit box With Facial Recognition: Fintech Case Study","year":2020,"lang":"en","type":"preprint","venue":"","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Raspberry pi; Arduino; Computer security; Computer science; Lock (firearm); Operating system; Embedded system; Engineering; Internet of Things","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":[0.0003151015,0.0005334851,0.0002629383,0.0004330183,0.001099731,0.0008126566,0.0007681451,0.002726204,0.005063884],"category_scores_gemma":[0.0009332489,0.0002234528,0.0003920818,0.0004305863,0.0007474626,0.0007349612,0.0005556502,0.0008718648,0.001325589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008543492,"about_ca_system_score_gemma":0.0005057737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00929393,"about_ca_topic_score_gemma":0.01826285,"domain_scores_codex":[0.9995103,0.00008639717,0.00002790091,0.00008431621,0.0001845993,0.0001065069],"domain_scores_gemma":[0.9996908,0.0001022613,0.00003368788,0.00003976532,0.00005822363,0.00007522486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009704749,0.00308122,0.07783207,0.0006253326,0.0001336083,0.5891185,0.007178663,0.01572241,0.02621331,0.007552723,0.03113724,0.2404345],"study_design_scores_gemma":[0.0001334695,0.001767269,0.07208195,0.0002552449,0.0001686321,0.6750284,0.01700938,0.07643686,0.06601698,0.004647308,0.08623859,0.0002159687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9472384,0.0007418056,0.01957946,0.002228527,0.0001024155,0.0001693122,0.0004621733,0.0003145472,0.02916333],"genre_scores_gemma":[0.9659997,0.0004862293,0.007441168,0.0003990319,0.00003072815,0.00003620191,0.0001947383,0.00004760313,0.02536459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00929393,"threshold_uncertainty_score":0.0184797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0253391563749274,"score_gpt":0.2271170277743028,"score_spread":0.2017778713993754,"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."}}