{"id":"W4417049897","doi":"10.1177/10806032251398832","title":"Voice-Calling Detection Distance with a Parabolic Microphone in Land Search and Rescue","year":2025,"lang":"en","type":"article","venue":"Wilderness and Environmental Medicine","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Microphone; Loudness; Intelligibility (philosophy); Active listening; Range (aeronautics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001236213,0.00009585806,0.0001412441,0.00007506921,0.00009811578,0.00003152592,0.0000916022,0.00003163736,0.000001992856],"category_scores_gemma":[0.000004478866,0.00006930302,0.000004911304,0.0001657393,0.0001751976,0.0001376942,0.00007448538,0.0001140547,8.359851e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002898483,"about_ca_system_score_gemma":0.000007695287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002554347,"about_ca_topic_score_gemma":0.0003104907,"domain_scores_codex":[0.9992992,0.0000193303,0.0001113183,0.0002840907,0.0001218951,0.0001641587],"domain_scores_gemma":[0.9997857,0.00002398378,0.00001406489,0.0001191909,0.000002125224,0.00005497712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001218007,0.00008732062,0.3862658,0.0001801387,0.00001939579,0.00008052742,0.001958338,0.0003267887,0.1250394,0.0000601372,0.000006499818,0.4858539],"study_design_scores_gemma":[0.004133704,0.0003078989,0.8775669,0.001208936,0.00001973202,0.0001148746,0.0009914312,0.02441069,0.0893368,0.0005821862,0.001004287,0.0003225908],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8798909,0.003641581,0.1155042,0.0007823952,0.00003963618,0.00007790006,5.610126e-7,0.00001385456,0.00004903114],"genre_scores_gemma":[0.9974043,0.0008498747,0.001416747,0.0001881559,0.00002860702,0.000008053874,0.000001433471,0.000004181812,0.00009860411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.491301,"threshold_uncertainty_score":0.2826095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005262765176506029,"score_gpt":0.2096845807067448,"score_spread":0.2044218155302387,"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."}}