{"id":"W4389329870","doi":"10.1139/dsa-2023-0051","title":"LidarBoX: a 3D-printed, open-source altimeter system to improve photogrammetric accuracy for off-the-shelf drones","year":2023,"lang":"en","type":"article","venue":"Drone Systems and Applications","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research; Oregon State University","keywords":"Drone; Computer science; Lidar; Global Positioning System; Remote sensing; Photogrammetry; Altimeter; Reliability (semiconductor); Real-time computing; Open source; Artificial intelligence; Geography; Telecommunications; Software","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0004796729,0.0007733156,0.0004254839,0.0009587237,0.0002783469,0.0006572332,0.00134415,0.000568133,0.01185951],"category_scores_gemma":[0.001952133,0.0003870999,0.0004327467,0.0003690758,0.0002815387,0.001199415,0.001559709,0.0006617864,0.005577666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002779978,"about_ca_system_score_gemma":0.0004516422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001233726,"about_ca_topic_score_gemma":0.001828641,"domain_scores_codex":[0.9993485,0.00006798721,0.00004693142,0.000109495,0.0003731236,0.00005402423],"domain_scores_gemma":[0.9990224,0.0001803944,0.00009870311,0.0002858224,0.0003293038,0.00008337612],"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":[0.0005947305,0.0002999497,0.01152088,0.001135335,0.0001303816,0.0008979906,0.0008884468,0.01668984,0.2617298,0.005443341,0.05029164,0.6503777],"study_design_scores_gemma":[0.0004049186,0.001468157,0.0220352,0.000429083,0.0002166274,0.002034998,0.0004502403,0.1686245,0.3822655,0.002849421,0.4188147,0.0004065879],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1078971,0.0008530047,0.8002543,0.0004372206,0.000683116,0.0007023698,0.00399587,0.0610225,0.02415453],"genre_scores_gemma":[0.5044048,0.0006752227,0.4541302,0.0005908817,0.0001250115,0.0008013354,0.006243289,0.004362787,0.02866641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01185951,"threshold_uncertainty_score":0.03967398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01544151023867392,"score_gpt":0.2514440581032727,"score_spread":0.2360025478645988,"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."}}