{"id":"W4213430843","doi":"10.1016/j.atech.2022.100042","title":"The digitization of agricultural industry – a systematic literature review on agriculture 4.0","year":2022,"lang":"en","type":"article","venue":"Smart Agricultural Technology","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":484,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Agriculture; Digitization; Context (archaeology); Business; Systematic review; Food security; Population; Emerging technologies; Marketing; Engineering; Computer science; Geography; Political science; Telecommunications; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0154901,0.001182478,0.003859297,0.02384976,0.0009926656,0.004369695,0.001720792,0.001940713,0.004614769],"category_scores_gemma":[0.05849155,0.0009781963,0.005958026,0.02079845,0.001317997,0.004319295,0.002551285,0.001545679,0.0004575608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005626316,"about_ca_system_score_gemma":0.0248981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008992326,"about_ca_topic_score_gemma":0.03058729,"domain_scores_codex":[0.9828908,0.005891995,0.005840155,0.001168233,0.003771797,0.0004369463],"domain_scores_gemma":[0.9269454,0.05617545,0.008959992,0.001326518,0.006045564,0.0005469047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000073084,0.00002372742,0.001231913,0.9169981,0.002323659,0.0001571574,0.0008733211,0.0001358482,0.000205539,0.001027268,0.002196218,0.07475404],"study_design_scores_gemma":[0.00003494073,0.00009509732,0.003937633,0.9493079,0.01091577,0.0004110342,0.0007723336,0.00006728173,0.0001538972,0.000516564,0.03375985,0.00002759283],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001245693,0.9962339,0.0003502134,0.0006046051,0.0001692871,0.0003543119,0.0004018152,0.000008856694,0.0006313088],"genre_scores_gemma":[0.01143072,0.9856749,0.001175483,0.000650582,0.00007911331,0.0005558337,0.0003029832,0.000005707485,0.0001247246],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9761502,"threshold_uncertainty_score":0.08192044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006871067030973965,"score_gpt":0.1957044890664615,"score_spread":0.1888334220354875,"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."}}