{"id":"W2961252543","doi":"10.1109/isass.2019.8757707","title":"A Survey on Forest Fire Monitoring Using Unmanned Aerial Vehicles","year":2019,"lang":"en","type":"article","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Damages; Flexibility (engineering); Fire detection; Computer science; Remote sensing; Environmental science; Firefighting; Environmental resource management; Engineering; Architectural engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001351194,0.0001053844,0.0001310165,0.00004200467,0.00003871884,0.00003510847,0.00006669998,0.00007361212,0.00005458601],"category_scores_gemma":[0.00001339289,0.00009887187,0.00003985404,0.0001148951,0.000004787667,0.00006972671,0.0000109752,0.00008507885,0.0003475977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006394995,"about_ca_system_score_gemma":0.000005932146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000773224,"about_ca_topic_score_gemma":0.0001461252,"domain_scores_codex":[0.9994255,0.00002854483,0.0001476096,0.0001133168,0.0001148682,0.0001701282],"domain_scores_gemma":[0.9997011,0.00005459363,0.0000140084,0.0001656735,0.00001936768,0.00004524747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001560302,0.00003733022,0.5193238,0.0001707562,0.0001172096,0.000008767114,0.0003750332,0.4227392,0.04624758,0.0001176812,0.001513065,0.009193494],"study_design_scores_gemma":[0.0005641896,0.00006593983,0.4680981,0.0000836177,0.000003358379,0.00000360085,0.00008125174,0.5198855,0.009186619,0.00000581454,0.00175302,0.0002689483],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933093,0.00002963682,0.0001797679,0.000005264193,0.003333404,0.0001270753,0.000005200222,0.0003301072,0.002680206],"genre_scores_gemma":[0.9989793,0.000004162449,0.00005541023,0.00000671353,0.0002785708,0.000002632756,0.000003684353,0.00002929145,0.000640287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09714628,"threshold_uncertainty_score":0.4467781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02622813269794623,"score_gpt":0.232985215962171,"score_spread":0.2067570832642248,"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."}}