{"id":"W3195900840","doi":"10.5772/intechopen.99862","title":"Artificial Intelligence and Big Data Analytics in Vineyards: A Review","year":2021,"lang":"en","type":"review","venue":"IntechOpen eBooks","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Big data; Computer science; Analytics; Data science; Domain (mathematical analysis); Artificial intelligence; Subject-matter expert; Applications of artificial intelligence; Expert system; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008593109,0.0004285846,0.001627973,0.00003468999,0.000109181,0.0002641682,0.001423627,0.0002753092,0.0002546499],"category_scores_gemma":[0.0008687403,0.0001341855,0.0002371404,0.0005860035,0.0001479539,0.0001012008,0.001689467,0.0007809714,0.00008313621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000714905,"about_ca_system_score_gemma":0.00008675738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003805881,"about_ca_topic_score_gemma":0.003326715,"domain_scores_codex":[0.9968674,0.0003351971,0.000997094,0.0009309554,0.0003911638,0.0004782563],"domain_scores_gemma":[0.998669,0.0004495673,0.000200885,0.000332548,0.0001461908,0.0002018563],"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":[0.000001426777,0.0000242187,5.951472e-7,0.002370662,0.00003035862,0.00006656514,0.000007298934,7.008252e-9,0.00003070516,0.0001171777,0.0005732376,0.9967778],"study_design_scores_gemma":[0.000006834476,0.0000600951,0.000002957693,0.04511082,0.0001366852,0.00007859762,0.00008509524,0.000005844485,0.00002160225,0.0001160491,0.954012,0.0003633712],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003356292,0.9965125,0.000002035871,0.00045694,0.000113012,0.001037609,0.000264879,0.00003153913,0.001547962],"genre_scores_gemma":[0.0001515872,0.9975221,0.00003400756,0.0001993182,0.0003677165,0.00009333008,0.000824761,0.0000029205,0.0008042352],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9964144,"threshold_uncertainty_score":0.5471926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.517286994981091,"score_gpt":0.4309705038517183,"score_spread":0.08631649112937267,"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."}}