{"id":"W4200584442","doi":"10.32920/17315693.v1","title":"Improving Fire Safety Systems Based On Internet Of Things And Deep Learning","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Firefighting; Smoke; Internet of Things; Fire safety; Computer science; Fire protection; The Internet; Architectural engineering; Snapshot (computer storage); Computer security; Simulation; Real-time computing; Aeronautics; Engineering; Civil engineering; World Wide Web; Operating system; Geography; Cartography","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":[0.0003366996,0.0002722006,0.000493841,0.0001128497,0.0000354346,0.0001183863,0.0001313005,0.000346062,0.0000717588],"category_scores_gemma":[0.00007078691,0.0002667597,0.0001213598,0.00007884354,0.00001837275,0.00006387552,0.0001452154,0.0008006235,0.000005681957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201468,"about_ca_system_score_gemma":0.00002255247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362729,"about_ca_topic_score_gemma":0.00002726604,"domain_scores_codex":[0.9986742,0.00009395658,0.000511345,0.0003300187,0.0002145168,0.0001759882],"domain_scores_gemma":[0.9993082,0.0001165575,0.0001299556,0.0003049104,0.00006799496,0.00007234442],"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":[0.00004084297,0.00001956752,0.0005041399,0.007930576,0.0001687436,0.00002074125,0.002259763,0.92544,0.001577716,0.00008278582,0.00007481679,0.06188029],"study_design_scores_gemma":[0.0002030705,0.00003965076,0.0002580689,0.0009941377,0.00001748473,0.000009218326,0.0006493369,0.9955541,0.0007605143,7.011128e-7,0.001263537,0.0002501147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2183316,0.005730038,0.7113444,0.00007340677,0.008738442,0.001277708,0.00001454882,0.002311633,0.05217818],"genre_scores_gemma":[0.9981925,0.00007823016,0.0005232102,0.00002338246,0.00006949989,0.00001561105,0.00003551876,0.00005573898,0.001006249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7798609,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005746415966130671,"score_gpt":0.1796836354198048,"score_spread":0.1739372194536741,"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."}}