{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001169004,0.0002753313,0.0001741595,0.0009404939,0.000366921,0.0003819573,0.0002711461,0.0002092662,0.0009951741],"category_scores_gemma":[0.0001893125,0.00009918999,0.0002024266,0.0007077212,0.0001231116,0.0001411999,0.0001953755,0.0001015582,0.0003404921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007046715,"about_ca_system_score_gemma":0.0008839175,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4641695,"about_ca_topic_score_gemma":0.7303701,"domain_scores_codex":[0.9999222,0.000004750852,0.000002116324,0.00002164332,0.00001637923,0.00003294774],"domain_scores_gemma":[0.9998854,0.00001298692,0.00001321773,0.000004643966,0.00007048663,0.00001323333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003187897,0.0001330011,0.7424929,0.000177832,0.0001569775,0.0005789743,0.0008701087,0.007860272,0.10449,0.0001985334,0.003542936,0.1391796],"study_design_scores_gemma":[0.000004107721,0.00001629054,0.9718703,0.0000179158,0.00002689475,0.0000427081,0.0005539516,0.0219282,0.004236502,0.0000170135,0.001277079,0.000009041421],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952638,0.0001444169,0.001839351,0.00002294376,0.00001008663,0.00001368058,0.001285897,0.00007349392,0.001346425],"genre_scores_gemma":[0.9923834,0.00009376476,0.003753607,0.00001498075,0.000005956321,0.00001268212,0.002180782,0.00001086009,0.001544045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5358305,"threshold_uncertainty_score":0.9229354,"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."}}