{"id":"W4226185317","doi":"10.1109/cogmi52975.2021.00010","title":"FireWarn: Fire Hazards Detection Using Deep Learning Models","year":2021,"lang":"en","type":"article","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Royal Military College of Canada; Queen's University","funders":"Defence Research and Development Canada","keywords":"Smoke; Fire detection; Convolutional neural network; Computer science; Artificial intelligence; Deep learning; Bounding overwatch; Contextual image classification; Pattern recognition (psychology); Test set; Image (mathematics); Computer vision; Remote sensing; Engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008554564,0.0001194042,0.0001388022,0.00004165187,0.0001375273,0.00005190849,0.00004211305,0.0001079672,0.0003015563],"category_scores_gemma":[0.00002003079,0.0001297458,0.00008031372,0.0002537911,0.00000751649,0.0001895687,0.00001785951,0.0002002139,0.00006853988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081098,"about_ca_system_score_gemma":0.00001324773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007470734,"about_ca_topic_score_gemma":0.0001540446,"domain_scores_codex":[0.9992822,0.00003985211,0.0001911037,0.0001558673,0.0001374159,0.0001935296],"domain_scores_gemma":[0.9996989,0.00001959302,0.00001705886,0.0001426948,0.00005859153,0.00006311788],"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":[0.00000239734,0.000004762615,0.0000499533,0.00004654778,0.0000283866,0.00001855352,0.0002808269,0.9020268,0.02072647,0.00002658678,0.00003198026,0.07675678],"study_design_scores_gemma":[0.0001316495,0.000009332535,0.00007716921,0.00001772797,0.000007888928,0.0002083573,0.0003182799,0.975593,0.01764246,0.00003981893,0.005795064,0.000159289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.538284,0.0007576587,0.4344678,0.0000199713,0.001164651,0.00007214922,7.558846e-7,0.0009865782,0.02424649],"genre_scores_gemma":[0.9968649,0.00005557822,0.0006972128,0.00002340233,0.0001292209,0.000005733582,0.000002976956,0.00003572431,0.002185263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4585809,"threshold_uncertainty_score":0.5290881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902053814283873,"score_gpt":0.205248325788981,"score_spread":0.1862277876461423,"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."}}