{"id":"W4323343857","doi":"10.5220/0011691200003417","title":"Environmental Information Extraction Based on YOLOv5-Object Detection in Videos Collected by Camera-Collars Installed on Migratory Caribou and Black Bears in Northern Quebec","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Northern Studies; Université Laval","funders":"","keywords":"Extraction (chemistry); Object (grammar); Geography; Object detection; Remote sensing; Computer science; Environmental science; Artificial intelligence; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004245115,0.0001720591,0.0001498927,0.0004174686,0.00003291257,0.00002124789,0.00005530454,0.0002098683,0.000008529908],"category_scores_gemma":[0.00009395065,0.0001833684,0.00002282442,0.0005839026,0.00005097425,0.0002701731,0.00001309538,0.0003080387,0.0000372848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009289728,"about_ca_system_score_gemma":0.000006286787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001064032,"about_ca_topic_score_gemma":0.04891546,"domain_scores_codex":[0.9991632,0.00001902319,0.0002628262,0.0001611231,0.0001690182,0.000224819],"domain_scores_gemma":[0.9996618,0.000122714,0.00003906124,0.0001385306,0.000005627011,0.0000322854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001581926,0.0000582344,0.00817713,0.00003926962,0.000012134,0.00001029357,0.0003636479,0.3376425,0.6234163,0.000002142608,0.000300463,0.02981971],"study_design_scores_gemma":[0.001540138,0.0001406334,0.08223052,0.00003926376,0.00000447949,0.00000123437,0.00156467,0.2060011,0.7068893,0.00002623135,0.001214282,0.0003480439],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998362,0.00001049166,0.0001996446,0.00004830293,0.00004359173,0.0003607864,0.00002270542,0.0006615755,0.0002908731],"genre_scores_gemma":[0.9996474,0.0000594566,0.00004820203,0.00004814213,0.000004121343,0.00006032629,0.00007231671,0.00002164252,0.00003840006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1316413,"threshold_uncertainty_score":0.9684393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003067237035590424,"score_gpt":0.1801795967640997,"score_spread":0.1771123597285093,"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."}}