{"id":"W3092550584","doi":"10.5194/egusphere-egu2020-20511","title":"The application of airborne remote sensing during an On-Site Inspection","year":2020,"lang":"en","type":"article","venue":"","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Bespoke; Remote sensing; Identification (biology); Computer science; Sensor fusion; Environmental science; Real-time computing; Artificial intelligence; 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":[0.00002705872,0.00005259562,0.00005468232,0.000007093948,0.0001996266,0.00002239352,0.00006205426,0.000008698002,0.000009116994],"category_scores_gemma":[7.140874e-7,0.00004044662,0.00003390783,0.0001253514,0.00002287071,0.00004393386,0.00001977211,0.00006481001,0.00005839723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005532777,"about_ca_system_score_gemma":0.000006151338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002084552,"about_ca_topic_score_gemma":0.000004951276,"domain_scores_codex":[0.9996249,0.0000100084,0.0001021898,0.0001273316,0.00006415296,0.00007142811],"domain_scores_gemma":[0.9996598,0.00001436565,0.00006309208,0.0001890586,0.00003288001,0.0000407438],"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":[0.00002599293,0.00004931089,0.0003807243,0.000005872895,0.00002609078,5.278128e-8,0.0003916254,0.0005555179,0.1591926,0.3577424,0.0001831889,0.4814466],"study_design_scores_gemma":[0.000949842,0.000178408,0.03453336,0.00001926929,0.00004392227,5.13409e-7,0.001516614,0.5918924,0.290159,0.04674638,0.03350835,0.0004519894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861285,0.000001711765,0.1198297,0.001436758,0.00001495216,0.0001657275,0.000006471082,0.00006838734,0.0171913],"genre_scores_gemma":[0.9987346,7.359839e-7,0.000874386,0.00005792554,0.0002745215,8.099768e-7,0.00001070783,0.00001042674,0.0000358758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5913369,"threshold_uncertainty_score":0.1649365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009156527901559982,"score_gpt":0.2350237223988922,"score_spread":0.2258671944973322,"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."}}