{"id":"W6888446611","doi":"10.21227/h2zw-pq68","title":"Aerial Fire and Smoke Essential","year":2025,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Smoke; Aerial photos; Fire detection; Aerial photography; Aerial survey","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004307515,0.000673294,0.0008259426,0.0002897744,0.0001838248,0.0002513867,0.001214573,0.0006699449,0.001160279],"category_scores_gemma":[0.0002029213,0.0007096751,0.000118108,0.0003576805,0.000289407,0.0003089429,0.0007049849,0.000772466,0.00120867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000918419,"about_ca_system_score_gemma":0.0006763965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004679182,"about_ca_topic_score_gemma":0.0008790767,"domain_scores_codex":[0.996742,0.00009714121,0.0006479872,0.001216021,0.0007005974,0.0005963076],"domain_scores_gemma":[0.9964669,0.00007477176,0.0003943243,0.002749151,0.00008990486,0.0002249281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001287461,0.0001138851,0.00001952365,0.0003016433,0.0002106016,0.0004860049,0.000003917488,6.176116e-7,0.00008907228,0.0000028458,0.9984617,0.0001814192],"study_design_scores_gemma":[0.0007669787,0.00003052601,0.0000774808,0.0001713181,0.0006146113,0.00007261621,0.000004641531,0.000005821629,0.0001824008,0.00001206428,0.9974185,0.000643092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008936339,0.0001815907,0.000002237465,0.00002473055,0.006213138,0.000485168,0.9918875,0.0001414569,0.0001705816],"genre_scores_gemma":[0.00003925872,0.0002981402,0.00003299697,0.000186821,0.002530979,0.00006309095,0.9961427,0.00005827207,0.0006477273],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004255251,"threshold_uncertainty_score":0.9997528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0183659946463138,"score_gpt":0.3050828624830231,"score_spread":0.2867168678367092,"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."}}