{"id":"W4393310176","doi":"10.1051/e3sconf/202450701060","title":"Smart garden with intruder detection system","year":2024,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Business; Environmental science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003757331,0.0006975846,0.001053928,0.001065685,0.000449173,0.0008223425,0.001101907,0.00091539,0.01250107],"category_scores_gemma":[0.0008366908,0.0003052389,0.0004585309,0.0004527952,0.0001747657,0.001111909,0.001120525,0.000429989,0.006469734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003036819,"about_ca_system_score_gemma":0.0003788683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001159941,"about_ca_topic_score_gemma":0.001168367,"domain_scores_codex":[0.9994037,0.0000510776,0.00005568664,0.0001789698,0.0002349496,0.0000756913],"domain_scores_gemma":[0.9993917,0.0000717915,0.00009319716,0.0001114113,0.0002571698,0.00007470093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001817751,0.001123524,0.04220723,0.001173552,0.0002611345,0.004466538,0.0008016139,0.007455308,0.1497294,0.00354247,0.09553481,0.6918868],"study_design_scores_gemma":[0.0007284611,0.003825238,0.1128172,0.0004486117,0.0009021235,0.01746382,0.0008717723,0.3744939,0.1908744,0.005238494,0.2917809,0.0005551298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3140847,0.0033369,0.4897606,0.001333315,0.00126316,0.002566815,0.005780396,0.1067571,0.07511697],"genre_scores_gemma":[0.8668528,0.0009265539,0.07543492,0.0008804393,0.0002033021,0.0007683922,0.004627859,0.0003334848,0.04997238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01250107,"threshold_uncertainty_score":0.04182023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064093654827642,"score_gpt":0.1860733888887738,"score_spread":0.1754324523404973,"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."}}