{"id":"W4387262579","doi":"10.3390/agronomy13102536","title":"“Smart Agriculture” Information Technology and Agriculture Cross-Discipline Research and Development","year":2023,"lang":"en","type":"article","venue":"Agronomy","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Jilin Agricultural University","keywords":"Phenomics; Agriculture; Data science; Precision agriculture; Computer science; Biotechnology; Genomics; Knowledge management; Biology; Ecology","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":[0.00292433,0.0004365878,0.000498538,0.001615554,0.001668956,0.007743522,0.0006804275,0.002709495,0.006522005],"category_scores_gemma":[0.003335295,0.0001980112,0.0003414692,0.003645389,0.009848075,0.008514668,0.004396501,0.002894271,0.002055883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00231463,"about_ca_system_score_gemma":0.004303517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001374401,"about_ca_topic_score_gemma":0.001722689,"domain_scores_codex":[0.9980168,0.0006623433,0.0001177679,0.0003554763,0.0006317809,0.0002158584],"domain_scores_gemma":[0.9971824,0.0009945126,0.0003417043,0.0004933042,0.0006011594,0.0003869011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002128915,0.00003863623,0.001373369,0.0003543359,0.0000264494,0.0001134164,0.001003448,0.0004820115,0.001207708,0.7816459,0.06405675,0.1496767],"study_design_scores_gemma":[0.000006841976,0.00005126522,0.002141411,0.000405107,0.00001633552,0.0002719664,0.0009915265,0.0005634804,0.0008774859,0.2698247,0.7248259,0.00002400835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02213644,0.08971423,0.08404438,0.3019411,0.01550284,0.0001688333,0.0003683651,0.0009778212,0.4851459],"genre_scores_gemma":[0.5142453,0.1203374,0.09966893,0.1153706,0.01210014,0.0003058591,0.0007397727,0.000305983,0.1369261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007743522,"threshold_uncertainty_score":0.02181828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03182323223326641,"score_gpt":0.2751644306940218,"score_spread":0.2433411984607554,"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."}}