{"id":"W3213681136","doi":"10.3390/drones5040132","title":"A Practical Validation of Uncooled Thermal Imagers for Small RPAS","year":2021,"lang":"en","type":"article","venue":"Drones","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Remote sensing; Black-body radiation; Environmental science; Vegetation (pathology); Thermal; Wind speed; Range (aeronautics); Calibration; Humidity; Computer science; Meteorology; Materials science; Optics; Physics; Geology","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":[0.0016005,0.0008056163,0.0004152327,0.0005302368,0.0004404144,0.0007494575,0.001498195,0.000756164,0.001531109],"category_scores_gemma":[0.002617034,0.0004234288,0.0005441526,0.0003583463,0.0006428959,0.001066131,0.0009880756,0.0009496938,0.0008657966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825065,"about_ca_system_score_gemma":0.0004142932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008582535,"about_ca_topic_score_gemma":0.00160618,"domain_scores_codex":[0.9985273,0.0002751645,0.00004725704,0.0003378317,0.0006969111,0.0001155087],"domain_scores_gemma":[0.9982892,0.0003538175,0.0002170178,0.0005099337,0.0005538066,0.00007615506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002395845,0.0001003089,0.005316549,0.0001747863,0.00004129001,0.000164855,0.0003352331,0.003461076,0.9437814,0.0007652612,0.0005409257,0.04507884],"study_design_scores_gemma":[0.00003080219,0.0007278227,0.01947847,0.0000476788,0.00005643614,0.0005282413,0.0001880767,0.03018899,0.941531,0.0003290358,0.00681443,0.00007912788],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4440172,0.0005465408,0.5462869,0.0001550749,0.0001247502,0.0004005612,0.0004827265,0.003084002,0.004902193],"genre_scores_gemma":[0.6936777,0.0002226795,0.3024455,0.0001404017,0.00002907817,0.0003103343,0.0005337634,0.0004288634,0.002211628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0016005,"threshold_uncertainty_score":0.008464396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176863095005401,"score_gpt":0.2571282104947507,"score_spread":0.2353595795446966,"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."}}