{"id":"W4297973258","doi":"10.3390/f13101591","title":"Evaluation of Positioning Accuracy of Smartphones under Different Canopy Openness","year":2022,"lang":"en","type":"article","venue":"Forests","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"GNSS applications; Global Positioning System; Deciduous; Precise Point Positioning; Computer science; Remote sensing; Mode (computer interface); Openness to experience; Environmental science; Geography; Telecommunications; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003462765,0.00004561267,0.00007178917,0.00002198026,0.0001283051,0.000004665987,0.0001088394,0.0000113548,0.001116268],"category_scores_gemma":[0.00002807549,0.00004242803,0.00002864524,0.0001445695,0.00005248885,0.000043618,0.0001207081,0.00004392617,0.00001141978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001380419,"about_ca_system_score_gemma":0.00002048525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008955045,"about_ca_topic_score_gemma":0.001103874,"domain_scores_codex":[0.9990587,0.00009948161,0.0001334403,0.000110052,0.0005230791,0.00007520579],"domain_scores_gemma":[0.9996288,0.00004541147,0.0001074477,0.0001757772,0.00002078778,0.00002176288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00004939256,0.0005836289,0.1926766,0.00002049281,0.00006113759,8.166705e-7,0.00290092,0.5255681,0.1844622,0.002364374,0.002483811,0.08882855],"study_design_scores_gemma":[0.0002494091,0.00004252742,0.9580504,0.000006836564,0.00004281598,0.000004321579,0.0002134514,0.02139171,0.0150271,0.004682998,0.0002260487,0.00006233152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954267,0.00001861491,0.0005663919,0.0001328739,0.00006352735,0.0001842742,0.00000959485,0.000007193084,0.003590902],"genre_scores_gemma":[0.9996862,0.000001023574,0.0001586043,0.0000165128,0.000007328581,0.00001170782,0.00002463295,0.00000538927,0.00008853189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7653739,"threshold_uncertainty_score":0.9997969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02656990392873381,"score_gpt":0.2862563254260735,"score_spread":0.2596864214973397,"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."}}