{"id":"W7082966317","doi":"10.15482/usda.adc/29922011.v1","title":"Data from: Avian Sentinels Neural Nest: AI-Powered Bird Monitoring System for Real-Time Detection and Species Identification","year":2025,"lang":"en","type":"dataset","venue":"Figshare","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Food and Agriculture","keywords":"Metadata; Software deployment; Artificial neural network; Population; Feature extraction; Identification (biology); Noise (video); Key (lock)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002639279,0.0008975232,0.0004813699,0.000613659,0.0002239749,0.000423947,0.0008803257,0.0005818845,0.00922041],"category_scores_gemma":[0.001065536,0.0002406188,0.0003579379,0.0003863683,0.0001360278,0.0007820931,0.0006619737,0.0006065227,0.005229236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003372279,"about_ca_system_score_gemma":0.0004176787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004180719,"about_ca_topic_score_gemma":0.00936024,"domain_scores_codex":[0.999786,0.00001379195,0.00001986991,0.00008322923,0.0000733386,0.00002383664],"domain_scores_gemma":[0.9995956,0.00004800705,0.00004019288,0.00007646642,0.000207354,0.00003251745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002267041,0.0005969125,0.03876189,0.001876468,0.0003460914,0.0007544049,0.0002788571,0.01239727,0.09675508,0.001678737,0.3994678,0.4448195],"study_design_scores_gemma":[0.0003415122,0.0009573728,0.1231295,0.0003547856,0.0002648046,0.001329387,0.000331452,0.3564441,0.21401,0.006135372,0.2963544,0.0003473951],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.231682,0.002084717,0.1756588,0.00177307,0.001630465,0.001271008,0.4032044,0.1459146,0.03678094],"genre_scores_gemma":[0.4301994,0.0007147957,0.151705,0.001434551,0.0001691937,0.001142813,0.3937274,0.002187788,0.01871901],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.00922041,"threshold_uncertainty_score":0.0308454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05958094700328857,"score_gpt":0.2827324984925546,"score_spread":0.223151551489266,"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."}}