{"id":"W2005177390","doi":"10.1080/10798587.2015.1015774","title":"Intelligent Information Technologies in Fruit Industry","year":2015,"lang":"en","type":"article","venue":"Intelligent Automation & Soft Computing","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Beijing; China; Chinese academy of sciences; Elite; Agriculture; Library science; Chinese society; Management; Political science; Computer science; Geography; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001377855,0.0006899156,0.0005070516,0.001953747,0.000730257,0.005102333,0.001076223,0.002275926,0.08586362],"category_scores_gemma":[0.002903985,0.0002750215,0.0004048769,0.00270735,0.0006388966,0.007551496,0.001930423,0.001721873,0.05278129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001010676,"about_ca_system_score_gemma":0.0008011578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008942666,"about_ca_topic_score_gemma":0.001007158,"domain_scores_codex":[0.9992965,0.0001531211,0.00005819734,0.0001153463,0.0002935242,0.00008316772],"domain_scores_gemma":[0.998639,0.0004045506,0.00007960902,0.0002108967,0.0004508025,0.0002150426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003339301,0.00005713613,0.0005290969,0.000421407,0.00001394576,0.0001349347,0.0001538446,0.0004247117,0.001508282,0.03616414,0.4855199,0.4750392],"study_design_scores_gemma":[0.00001001391,0.00003958828,0.0007865803,0.0002581668,0.00001026045,0.0001943441,0.0001612086,0.001409137,0.000752712,0.02955851,0.9668006,0.00001884764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005258098,0.109502,0.04961058,0.04891983,0.01167992,0.0003084261,0.001721645,0.007589441,0.7654101],"genre_scores_gemma":[0.0821042,0.1152188,0.06050225,0.01128259,0.008285144,0.0003800505,0.003615889,0.0009728976,0.7176381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08586362,"threshold_uncertainty_score":0.2872424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03491421312981086,"score_gpt":0.2494221863959179,"score_spread":0.214507973266107,"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."}}