{"id":"W4385628550","doi":"10.23977/jeis.2023.080302","title":"Forest Fire Protection System Based on LoRa Technology","year":2023,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"ALARM; Base station; Fire prevention; Environmental science; Smoke; Computer science; Real-time computing; Manual fire alarm activation; Transmission (telecommunications); Cloud computing; Point cloud; Remote sensing; Telecommunications; Meteorology; Engineering; Architectural engineering; Geography; Electrical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002322245,0.0004339702,0.0004172173,0.00075994,0.0006476862,0.0006251765,0.0006176028,0.0003476252,0.004481259],"category_scores_gemma":[0.0004066218,0.0001473394,0.000328914,0.0003002308,0.0001743988,0.0007510608,0.0006769958,0.0004305805,0.001946055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003636594,"about_ca_system_score_gemma":0.0004379335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002171816,"about_ca_topic_score_gemma":0.001398954,"domain_scores_codex":[0.9996693,0.00006002154,0.00001917665,0.00005697149,0.0001086491,0.00008582337],"domain_scores_gemma":[0.9997105,0.00003013805,0.00003583279,0.00004516782,0.0001396823,0.00003862531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001617713,0.0005743812,0.01829133,0.001157273,0.0002504093,0.001989617,0.001042785,0.02895833,0.2110988,0.01205871,0.08724978,0.6357109],"study_design_scores_gemma":[0.0006854745,0.002212597,0.01926519,0.0002614602,0.0006149945,0.00449479,0.0007095947,0.4426504,0.2458469,0.00474713,0.2780985,0.0004131393],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2515593,0.00333299,0.5868623,0.00173643,0.0009762864,0.000749339,0.001019363,0.05713833,0.09662569],"genre_scores_gemma":[0.9527753,0.000659482,0.02802001,0.0003256392,0.0001430027,0.000205928,0.0005119927,0.000146916,0.0172117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004481259,"threshold_uncertainty_score":0.01499128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005407625189596176,"score_gpt":0.1926989820185985,"score_spread":0.1872913568290023,"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."}}