{"id":"W4391185133","doi":"10.1109/ipcv57033.2023.00030","title":"Behavior Prediction of Vespa Mandarinia Based on Convolutional Neural Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Insect and Arachnid Ecology and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Artificial neural network; Machine learning","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":[0.0001093486,0.000331375,0.0001258812,0.0003257705,0.0001300763,0.0001996,0.000269703,0.0002012374,0.000563523],"category_scores_gemma":[0.000317134,0.0001120092,0.0002555336,0.0001224634,0.00009349592,0.0001666636,0.0001407165,0.0002167814,0.0001368748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004454417,"about_ca_system_score_gemma":0.000256847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0240217,"about_ca_topic_score_gemma":0.03626756,"domain_scores_codex":[0.9999603,0.000005529247,0.00000141716,0.00001720701,0.00000570447,0.000009755834],"domain_scores_gemma":[0.9999031,0.00003504701,0.00001969297,0.00000706869,0.00002586678,0.000009235211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004928767,0.0003529627,0.237232,0.0000984917,0.0001683243,0.0004037784,0.0001727791,0.4525651,0.08320313,0.001394588,0.003085183,0.2208308],"study_design_scores_gemma":[0.000002165278,0.00002297488,0.02646329,0.000004479339,0.00001282068,0.00003282658,0.00001396384,0.9701722,0.00285771,0.0002078744,0.0002055808,0.000004221068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636838,0.0002919011,0.0325543,0.0001743523,0.00001638882,0.0000154734,0.000407263,0.0002922535,0.002564267],"genre_scores_gemma":[0.9915181,0.00007096108,0.007009434,0.00002158592,0.000003290184,0.000006664113,0.0003349032,0.000005571326,0.001029562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0240217,"threshold_uncertainty_score":0.04776371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315413530670674,"score_gpt":0.2472473253360762,"score_spread":0.2340931900293695,"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."}}