{"id":"W4318559835","doi":"10.1101/2023.01.27.525894","title":"movedesign: Shiny R app to evaluate sampling design for animal movement studies","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Israel Institute for Biological Research; Sächsisches Staatsministerium für Wissenschaft und Kunst; Bundesministerium für Bildung und Forschung; National Science Foundation","keywords":"Computer science; Estimator; Range (aeronautics); Sampling (signal processing); Global Positioning System; Home range; Movement (music); Kernel density estimation; Statistical power; Sampling design; Autocorrelation; Distance sampling; Data mining; Statistics; Simulation; Ecology; Computer vision; Engineering; Mathematics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01815221,0.003144378,0.00240353,0.002778757,0.0006847911,0.002782381,0.004136941,0.001816822,0.116252],"category_scores_gemma":[0.06997199,0.002401827,0.002931101,0.001758242,0.001369889,0.002491646,0.003945931,0.003330541,0.04843061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107213,"about_ca_system_score_gemma":0.003392958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002472618,"about_ca_topic_score_gemma":0.003744819,"domain_scores_codex":[0.9944569,0.002356455,0.0006902173,0.0008759765,0.001302265,0.0003182665],"domain_scores_gemma":[0.9351521,0.05430516,0.002987187,0.003460407,0.003430518,0.0006646612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001561016,0.0001850726,0.005446077,0.004967417,0.001080761,0.0008110557,0.000833309,0.006768958,0.005712362,0.009447361,0.8705979,0.09258881],"study_design_scores_gemma":[0.003307514,0.000960541,0.01666225,0.003501107,0.001094279,0.001491391,0.0004099125,0.1225383,0.02918346,0.04810727,0.7718949,0.0008490207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.007223582,0.0007459552,0.286255,0.0009078642,0.0008037013,0.001867395,0.06071987,0.6355647,0.005911942],"genre_scores_gemma":[0.04086062,0.0006866508,0.5647049,0.002394559,0.0002264416,0.01658827,0.02902005,0.335345,0.01017344],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.116252,"threshold_uncertainty_score":0.3889016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09605411548079484,"score_gpt":0.2968512427343333,"score_spread":0.2007971272535384,"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."}}