{"meta":{"query_hash":"3ef2f6d9104e","filters":{"venue":"2022 E-Health and Bioengineering Conference (EHB)"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/3ef2f6d9104e","api":"https://metacan.xera.ac/api/v1/cohort?venue=2022+E-Health+and+Bioengineering+Conference+%28EHB%29"},"results":[{"id":"W4313527197","doi":"10.1109/ehb55594.2022.9991443","title":"Meteorological Data and UAV Images for the Detection and Identification of Grapevine Disease Using Deep Learning","year":2022,"lang":"en","type":"article","venue":"2022 E-Health and Bioengineering Conference (EHB)","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Providence Health Care","keywords":"Downy mildew; Computer science; Identification (biology); Deep learning; Artificial intelligence; Segmentation; Precision and recall; Machine learning; Remote sensing; Geography; Biology; Agronomy","score_opus":0.07250104154231839,"score_gpt":0.3074854720010975,"score_spread":0.2349844304587791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313527197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8369738,0.0030220016,0.13830577,0.0006144785,0.0004140549,0.00017295044,0.009058374,0.0057792915,0.005659322],"genre_scores_gemma":[0.9438011,0.00043648778,0.043914374,0.00008247828,0.000045083947,0.000040179606,0.009145351,0.000051546438,0.0024832643],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99980456,0.000021813246,0.000013171585,0.000073083094,0.00004130995,0.000045973786],"domain_scores_gemma":[0.99985135,0.00002802418,0.000019472041,0.000024433568,0.000057748304,0.000019116573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025384594,0.0008871821,0.00035283834,0.0012795499,0.00019964382,0.0004106614,0.00037801376,0.00063358963,0.0014021491],"category_scores_gemma":[0.00057853956,0.00019732007,0.0006015506,0.00064403814,0.00009880539,0.00052236946,0.00039014313,0.0004820668,0.00069399155],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006681046,0.00086208456,0.09305146,0.00045809775,0.0003822738,0.0011489458,0.00019427811,0.16355488,0.10316843,0.0007841027,0.01772099,0.6180064],"study_design_scores_gemma":[0.000014767906,0.00012064871,0.051243752,0.00003753378,0.00005784301,0.00014251958,0.00012440598,0.92822987,0.016504915,0.0005634281,0.0029338417,0.000026541018],"about_ca_topic_score_codex":0.011665897,"about_ca_topic_score_gemma":0.014971876,"teacher_disagreement_score":0.011665897,"about_ca_system_score_codex":0.00030976886,"about_ca_system_score_gemma":0.0002979843,"threshold_uncertainty_score":0.023196042},"labels":[],"label_agreement":null}]}