{"id":"W4417447589","doi":"10.1002/wlb3.01502","title":"Monitoring wildlife using long‐endurance solar‐electric UAVs","year":2025,"lang":"en","type":"article","venue":"Wildlife Biology","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Wildlife; Propulsion; Footprint; Drone; Aerial survey; Disturbance (geology); Wildlife conservation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001796295,0.0002469304,0.0001595453,0.0004016805,0.0001563891,0.0002327037,0.0002424613,0.000122682,0.0006693594],"category_scores_gemma":[0.0003281641,0.00007281523,0.0001485981,0.0002374099,0.00009279618,0.0004161248,0.0002080625,0.00007577278,0.0001283469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001305633,"about_ca_system_score_gemma":0.00008185302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029772,"about_ca_topic_score_gemma":0.002807151,"domain_scores_codex":[0.9999133,0.00001943436,0.000005134793,0.00002563262,0.00002820261,0.000008259021],"domain_scores_gemma":[0.9998091,0.00007643419,0.00003978676,0.00001633367,0.00004273298,0.00001560953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004265711,0.0001470921,0.09063701,0.0007813597,0.0002348132,0.0004518204,0.0002917418,0.0559887,0.2495927,0.0007872534,0.001497308,0.5991637],"study_design_scores_gemma":[0.0001019595,0.005092879,0.3673238,0.0003396786,0.0005475685,0.002057008,0.00199075,0.305232,0.2472129,0.002355778,0.0676206,0.0001250669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048964,0.00365302,0.08358741,0.00009820139,0.00006290813,0.00006919585,0.0001927324,0.0002957137,0.007144348],"genre_scores_gemma":[0.9741488,0.0008453196,0.02358364,0.00002339464,0.0000139169,0.00002229953,0.0001394835,0.00001335582,0.001209758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001029772,"threshold_uncertainty_score":0.002239227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244341937440419,"score_gpt":0.2581609694442527,"score_spread":0.2457175500698485,"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."}}