{"id":"W3121833776","doi":"10.4271/2021-01-0063","title":"Intelligent Voice Activated Drone(s) for in-Vehicle Services and Real-Time Predictions","year":2021,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Drone; Computer science; Voice communication; Real-time computing; Aeronautics; Computer network; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002190787,0.0003948306,0.0004675544,0.0001482812,0.0002251367,0.00009681519,0.0003179016,0.0004949361,0.0001936433],"category_scores_gemma":[0.000104266,0.0003954432,0.0001389717,0.0008170558,0.0002036024,0.000367179,0.0001579396,0.0004635769,0.00004423134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000218113,"about_ca_system_score_gemma":0.00004364468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004905912,"about_ca_topic_score_gemma":0.03471016,"domain_scores_codex":[0.9978589,0.00004439949,0.00064847,0.0006716534,0.00027568,0.0005009116],"domain_scores_gemma":[0.9985948,0.000315056,0.00007235105,0.0006990542,0.0001145913,0.0002041644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006494393,0.0001928429,0.0001125525,0.0001020627,0.00003441818,0.000005458171,0.00004121931,0.001690383,0.9920887,0.002904555,0.0006425107,0.002120326],"study_design_scores_gemma":[0.0006823154,0.000322764,0.9613331,0.0002221305,0.00007964428,0.00003659514,0.0001786419,0.00007074644,0.003658286,0.001494236,0.03134034,0.0005811846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558026,0.0006142599,0.00008900757,0.002774934,0.0001928916,0.001864997,0.0002051462,0.004469015,0.03398715],"genre_scores_gemma":[0.9880229,0.001789844,0.008528833,0.0002770504,0.00007873921,0.0006952708,0.0001857045,0.0001021151,0.0003195783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9884304,"threshold_uncertainty_score":0.9998497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007829126624687995,"score_gpt":0.2273303324889943,"score_spread":0.2195012058643064,"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."}}