{"id":"W2933072809","doi":"10.3390/drones3010028","title":"Applications of Unmanned Aerial Vehicles to Survey Mesocarnivores","year":2019,"lang":"en","type":"article","venue":"Drones","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Occupancy; Camera trap; Geography; Population; Aerial survey; Abundance (ecology); Wildlife; Cartography; Environmental science; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003707704,0.000343473,0.0001468113,0.0006574237,0.0001576818,0.000229175,0.0003086672,0.0001393655,0.000327717],"category_scores_gemma":[0.0008043128,0.0001522663,0.0001347527,0.0003945604,0.0001158103,0.000249408,0.0002990245,0.0001229521,0.00008773821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002048476,"about_ca_system_score_gemma":0.0003389076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008229642,"about_ca_topic_score_gemma":0.01737281,"domain_scores_codex":[0.9996793,0.00009269641,0.00001654803,0.0000685464,0.000114662,0.00002828041],"domain_scores_gemma":[0.9994776,0.0001442542,0.0001042878,0.0000676097,0.0001634144,0.00004292161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001564579,0.0001555301,0.2588677,0.0003441597,0.0001841647,0.0005110679,0.0007881588,0.04236389,0.1119425,0.0007217744,0.001436822,0.5825278],"study_design_scores_gemma":[0.00009479257,0.001967625,0.5266165,0.0001991077,0.0001856657,0.001293874,0.002476603,0.3762791,0.05879432,0.001970669,0.0299981,0.0001237275],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8698871,0.002218511,0.1212353,0.0002151503,0.00006652033,0.0004565505,0.0008152846,0.0007798654,0.004325742],"genre_scores_gemma":[0.8737941,0.0007281259,0.1244801,0.00006969058,0.00001846546,0.000105922,0.0002764313,0.00001414851,0.0005129659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008229642,"threshold_uncertainty_score":0.0163635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007873489969380674,"score_gpt":0.2225521938581919,"score_spread":0.2146787038888112,"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."}}