{"id":"W4393638968","doi":"10.5281/zenodo.4694325","title":"Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Hurricane katrina; Atlantic hurricane; Emergency response; History; Meteorology; Disaster response; Natural disaster; Oceanography; Geography; Emergency management; Tropical cyclone; Geology; Medical emergency; Political science; Law; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000442174,0.001242287,0.0006087138,0.003968939,0.0008819116,0.00113175,0.00104743,0.001377668,0.07103999],"category_scores_gemma":[0.001991465,0.000385013,0.0006848159,0.00325191,0.0003508573,0.001346641,0.001041911,0.001301986,0.07927824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170369,"about_ca_system_score_gemma":0.001058997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02992663,"about_ca_topic_score_gemma":0.07649743,"domain_scores_codex":[0.9994802,0.0000419276,0.00003645402,0.0001682535,0.0001767109,0.00009653382],"domain_scores_gemma":[0.9986111,0.0002473248,0.0001095267,0.0002996897,0.0006110347,0.0001213537],"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":[0.00004413229,0.0000284204,0.0006364778,0.0002526588,0.000008209473,0.00002205389,0.00004003671,0.0001489381,0.0004953378,0.0002050999,0.9912661,0.006852499],"study_design_scores_gemma":[0.00007396211,0.00001964932,0.01170834,0.0002869373,0.00001912541,0.00009570889,0.0004343777,0.001224709,0.00190048,0.0007623849,0.9834338,0.00004048632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00119899,0.0001459142,0.0004895231,0.0002242575,0.0002038113,0.00007544983,0.9875715,0.003332959,0.006757632],"genre_scores_gemma":[0.002124647,0.0000806238,0.002414258,0.0001016231,0.00004837624,0.0001054062,0.9911765,0.0006522536,0.003296265],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07103999,"threshold_uncertainty_score":0.2376524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0298315509142243,"score_gpt":0.232094429438497,"score_spread":0.2022628785242727,"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."}}