{"id":"W4396585407","doi":"10.3390/rs16091627","title":"SWIFT: Simulated Wildfire Images for Fast Training Dataset","year":2024,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Swift; Training (meteorology); Remote sensing; Environmental science; Computer science; Meteorology; Geology; Geography","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":[0.0001543284,0.0001439711,0.000164061,0.0001010826,0.00008267828,0.0001165727,0.00004443283,0.00008160096,0.000004782222],"category_scores_gemma":[0.00003133106,0.0001467344,0.00007222636,0.0001889872,0.000014591,0.0001116577,0.000009480974,0.0001435229,0.0000615482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005555627,"about_ca_system_score_gemma":0.00001352399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003880197,"about_ca_topic_score_gemma":0.00001304582,"domain_scores_codex":[0.9992451,0.00001566968,0.0002071689,0.0001932293,0.0000921844,0.0002466379],"domain_scores_gemma":[0.9996355,0.000103948,0.00001184961,0.0001776258,0.00001180502,0.00005930218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008476806,0.000001108303,1.60455e-7,0.0003065905,0.00008998307,0.00007362431,0.00115057,0.0434626,0.0426585,0.000008063631,0.01250698,0.8997334],"study_design_scores_gemma":[0.0001110902,0.000009253529,0.000003795739,0.000209666,0.00001475623,0.00008921348,0.0001573292,0.7971205,0.002245438,0.00003698292,0.1998604,0.0001416059],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1046014,0.00320609,0.8661189,0.0007661412,0.009102738,0.001061704,0.001511456,0.006390597,0.007240952],"genre_scores_gemma":[0.995718,0.00001933398,0.003233821,0.0000486403,0.0003755298,1.774223e-8,0.0003374559,0.0000712187,0.0001959695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8995917,"threshold_uncertainty_score":0.5983654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115629115829634,"score_gpt":0.2519840643115534,"score_spread":0.2308277731532571,"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."}}