{"id":"W2428243001","doi":"10.1139/juvs-2016-0008","title":"The future of UAVs in ecology: an insider perspective from the Silicon Valley drone industry","year":2016,"lang":"en","type":"article","venue":"Journal of Unmanned Vehicle Systems","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drone; Insider; Silicon valley; Perspective (graphical); Ecology; Engineering; Business; Political science; Computer science; Biology; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004360143,0.00008639746,0.0001790181,0.00005178801,0.00006790442,0.00002908644,0.0002400898,0.0001805018,0.000009417],"category_scores_gemma":[0.00003189965,0.00004181981,0.00004523533,0.0001602477,0.00004423205,0.0001905779,0.00001526373,0.0003062627,0.000003715998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001594666,"about_ca_system_score_gemma":0.00004076681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001106814,"about_ca_topic_score_gemma":0.0003676864,"domain_scores_codex":[0.9991127,0.0001165439,0.0004209391,0.00007620738,0.0001462228,0.0001274194],"domain_scores_gemma":[0.9990849,0.00022794,0.0002165785,0.0002236057,0.0002019971,0.0000450049],"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":[0.0005760533,0.0007041403,0.2522501,0.0001002174,0.001363829,0.0000442627,0.01975199,0.5307754,0.1039248,0.03915486,0.01622701,0.03512739],"study_design_scores_gemma":[0.005709423,0.0007712269,0.7872818,0.0007351736,0.0001476368,0.0001145344,0.07472926,0.1032606,0.004977118,0.00522972,0.01642466,0.0006188951],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938897,0.002529581,0.0003975281,0.002318488,0.0004576899,0.0001710478,0.000009711744,0.00001424704,0.0002120343],"genre_scores_gemma":[0.9989194,0.0003459967,0.00005066133,0.00001847279,0.0006008677,0.000008790155,5.581371e-7,0.00001579903,0.00003940371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5350316,"threshold_uncertainty_score":0.1705362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007312790593613389,"score_gpt":0.2218222939793501,"score_spread":0.2145095033857367,"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."}}