{"id":"W3191485867","doi":"10.1002/rse2.234","title":"Multispecies detection and identification of African mammals in aerial imagery using convolutional neural networks","year":2021,"lang":"en","type":"article","venue":"Remote Sensing in Ecology and Conservation","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke; Computer Research Institute of Montréal","funders":"Fox Chase Cancer Center; Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture; Fonds De La Recherche Scientifique - FNRS; Centre for International Forestry Research; European Commission","keywords":"Convolutional neural network; Artificial intelligence; Pattern recognition (psychology); Aerial image; Object detection; Computer science; Biology; Image (mathematics)","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":[0.0003933269,0.00007507405,0.0001434702,0.00006894186,0.00009898128,0.00001199283,0.00002142057,0.0001485023,0.00001679496],"category_scores_gemma":[0.0002262453,0.00009204567,0.00001386746,0.0002559804,0.0002680169,0.0001912127,0.00004783546,0.0001188548,9.976191e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001065255,"about_ca_system_score_gemma":0.00002226749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008755624,"about_ca_topic_score_gemma":0.01331183,"domain_scores_codex":[0.9990034,0.0002353179,0.0003402672,0.0002245937,0.00005766412,0.0001387527],"domain_scores_gemma":[0.9995237,0.000196799,0.000158841,0.00007292075,0.0000284237,0.00001932047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009360433,0.00002211486,0.8967462,0.000008873537,0.00000550421,0.00001661482,0.0001902408,0.008527176,0.07290542,0.00004163006,0.000005807979,0.0214368],"study_design_scores_gemma":[0.0002293807,0.000008237672,0.5371728,0.000005999475,0.000005355254,0.00004155436,0.00007247792,0.4613943,0.0006375624,0.0003848145,0.000004872093,0.0000426882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932057,0.00003889436,0.005597642,0.0007715261,0.0002273694,0.0001153478,9.58463e-7,0.000008091637,0.00003452515],"genre_scores_gemma":[0.9982102,0.0000341415,0.001424945,0.0002665188,0.0000261505,3.485832e-7,0.000008857622,0.000004323696,0.00002452964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4528671,"threshold_uncertainty_score":0.7428312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01370773287799138,"score_gpt":0.2214576058031757,"score_spread":0.2077498729251843,"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."}}